CN106656303B - A kind of signal detecting method based on satellite antenna acquisition and tracking pointing system - Google Patents

Abstract

The invention belongs to the technical field of signal detection, and discloses a signal detection method based on a satellite-borne antenna capture tracking pointing system, comprising: dividing the frequency range to be detected into M frequency bands to be detected, and initializing; obtaining the i-th frequency band to be detected F For the sampling data of _i , use the sampling data to obtain the spectral data of the kth non-coherent accumulation, and perform K non-coherent accumulation to obtain the overall undetected decision data S _i ^K of F _i , and use S _i ^K to determine the detection threshold TH; determine The maximum value S _ijmax in the decision data S _ij to be detected of the jth channel; perform N times of detection according to S _ijmax and the detection threshold TH, and determine whether it is detected in the jth channel of F _i according to the results of N times of detection If the target signal is detected, then further determine the corresponding target signal bandwidth; otherwise, add 1 to the channel number j, and continue to detect the next channel until all channels of F _i are detected. The invention can realize the detection of weak signals in the space noise environment, and the detection time is short.

Description

A signal detection method based on satellite-borne antenna acquisition, tracking and pointing system

technical field

The invention relates to the technical field of signal detection, in particular to a signal detection method based on a satellite-borne antenna acquisition, tracking and pointing system.

Background technique

In the field of aerospace measurement and control communication technology, the completion of the Tracking and Data Relay Satellite System (TDRSS) has realized the space-based measurement and control communication of low-orbit spacecraft, solved the problem of high coverage of measurement and control, communication and Technical issues such as high-speed data transmission. The relay satellite antenna needs to realize the capture and tracking of various user satellites and establish inter-satellite links; for such an antenna pointing system (Antenna Pointing System, APS), the first and second generation relay satellite systems in the United States have chosen Under this scheme, it is a major technical problem to realize the autonomous closed-loop acquisition and tracking of user satellites on the satellite. However, with the development of the aerospace industry and the breakthrough of various technical problems, it is reasonable and feasible to use the satellite autonomous closed-loop antenna to capture, track and point to the system.

In the field of space information based on space-based measurement and control communication systems, the acquisition and confrontation of space information has become an important factor affecting the modern battlefield. In this context, it is relatively easy to adjust the antenna pointing based on the on-board autonomous closed-loop antenna acquisition tracking pointing system to realize the automatic acquisition and tracking of non-cooperative target satellites. However, for non-cooperative target satellites, the detailed parameters of the carrier frequency, bandwidth, modulation mode and code rate of the communication signal are unknown, which brings difficulties to the design of space signal acquisition and tracking.

Specifically, since the working frequency band of the non-cooperative target satellite is unknown, it is necessary to conduct a comprehensive detection of the possible working frequency band of the target satellite. The detection frequency band is relatively wide, so the signal is sampled and processed by step-sweep and digital channelization, and then the signal is detected. Although the application of high-gain antennas on the satellite can effectively improve the gain-to-noise ratio G/T of the received signal and enhance the ability to receive weak signals; however, the huge loss of radio signal long-distance transmission, spatial noise and interference will make the signal-noise of the received signal Relatively small, thus reducing the system's ability to detect weak signals. At the same time, the on-board acquisition and tracking system has a specified time requirement for the acquisition of the target satellite, so if it is necessary to process a large amount of signal data and complete the signal detection in a short period of time, the traditional sliding window constant false alarm detection method is It will no longer be applicable due to the long detection time.

SUMMARY OF THE INVENTION

In view of the above problems, the embodiments of the present invention provide a signal detection method based on the satellite-borne antenna acquisition tracking pointing system, which can realize the detection of weak signals in a space noise environment, and the detection time is short and the detection efficiency is high.

In order to achieve the above object, embodiments of the present invention adopt the following technical solutions:

A signal detection method based on a satellite-borne antenna capture tracking pointing system is provided, comprising the following steps:

Step 1: Obtain the frequency interval to be detected and the bandwidth index value of a single frequency interval to be detected, and then divide the frequency interval to be detected into M frequency bands to be detected F ₁ , F ₂ , ... according to the bandwidth index value C of a single frequency interval to be detected , F _M , go to step 2; where, C represents the bandwidth index value of a single frequency range to be detected, B _F represents the bandwidth of the frequency range to be detected, and [ ] represents rounding operation;

Step 2, initialization: make frequency sweep value i=1, channel number j=1, number of times of non-coherent accumulation k=1, number of times of detection n=1, number of times of detected targets p=0, set the total number of times of non-coherent accumulation K, Go to step 3;

Step 3, obtain the sampling data obtained by sampling the data of the ith frequency band F _i to be detected by the analog-to-digital converter and sample data Perform digital down-conversion processing, and then perform digital channelization processing on the sampled data after digital down-conversion processing to obtain channelized data of W channels

Fast Fourier transform is performed on the channelized data of W channels respectively to obtain the spectral data of W channels

Spectrum data for W channels First perform the point-by-point modulus operation, and then perform the square operation to obtain the spectral data corresponding to the kth non-coherent accumulation of W channels Go to step 4;

Step 4, judging whether the number k of non-coherent accumulation is equal to the total number K of non-coherent accumulation; if k≠K, add 1 to k, and go to step 3; if k=K, go to step 5;

Step 5: Sum the spectrum data corresponding to all K non-coherent accumulations of the qth channel among the W channels to obtain the decision data S _ij to be detected for the qth channel, where q takes all the values between 1 and W integer value;

Splicing the judgment data to be detected of all W channels according to the order of the channels to obtain the overall judgment data S _i ^K to be detected of the ith frequency band F _i to be detected;

Use the overall undetected decision data S _i ^K of the i-th frequency band F _i to be detected to determine the detection threshold TH; determine the maximum value S _{ij max} of the undetected decision data S _ij of the j-th channel, and judge the j-th channel The maximum value S _{ij max} in the decision data S _ij to be detected and the size of the detection threshold TH; if S _{ij max} >TH, go to step 6; if S _{ij max} ≤ TH, go to step 7;

Step 6: Add 1 to the number p of detected targets, and determine the maximum value S ij max of the jth channel’s decision data S _ij to be detected and the maximum value S _{ij max} of the jth channel’s decision data S _ij to be detected. The signal bandwidth corresponding to the j-th channel of the i-th detection frequency band F _i in the n-th detection Let the signal bandwidth corresponding to the jth channel of the ith detection frequency band F _i be Go to step 7;

Step 7, adding 1 to the number of detection times n, and judging whether the number of detection times n is less than or equal to the preset number of detection times N;

If the detection times n is less than or equal to the preset detection times N, go to step 3;

If the number of detections n is greater than the preset number of detections N, it is judged whether the number of detected targets p is greater than the preset value P; if p≤P, it is determined that there is no detection in the jth channel of the ith frequency band F _i to be detected to the target signal, let the signal bandwidth B _ij corresponding to the jth channel of the i-th detection frequency band F _i =0, go to step 8; otherwise, if p>P, then determine the i-th frequency band F _i to be detected If the target signal is detected in the jth channel, go to step 8;

Step 8, add 1 to the channel number j, and judge whether j is equal to the total number of channels W; if j=W, go to step 9, otherwise, go to step 5;

Step 9, determine whether a signal is detected in the W channels of the _i -th frequency band F to be detected; if no target signal is detected in the W channels of the _i -th frequency band F to be detected, then the frequency sweep value Add 1 to i and go to step 3; if the target signal is detected in w channels among the W channels of the i-to-be-detected frequency band F _i , go to step 10; where w is an integer, 1≤w≤W ;

Step 10, using the signal bandwidth corresponding to each of the w channels, the bandwidth B _F of the frequency interval to be detected, the number of channels W, and the number of frequency bands to be detected M, to determine the target signal bandwidth B _i .

Based on the signal detection method based on the satellite-borne antenna acquisition tracking pointing system provided by the above-mentioned embodiments of the present invention, on the one hand, due to the use of non-coherent accumulation to improve the signal-to-noise ratio, compared with coherent accumulation, the embodiment of the present invention adopts The engineering implementation of non-coherent accumulation is relatively simple, and the amount of calculation is relatively small, and for fast-fluctuating received signals, non-coherent accumulation will also obtain better detection results. Therefore, the embodiment of the present invention provides The signal detection method of the tracking and pointing system can realize the detection of weak signals in the space noise environment. On the other hand, the existing technology adopts the scheme of detecting the whole to-be-detected interval, and the data in the entire to-be-detected interval needs to be processed during the detection. Due to the large amount of data, it will take a long time to read/write data , so that the detection time is longer and the detection efficiency is lower; and different from the prior art, the signal detection method based on the satellite-borne antenna capture tracking and pointing system provided by the embodiment of the present invention does not use the overall detection method in the prior art Each detection unit in the interval detects the scheme point by point, but divides the whole interval to be detected into several frequency bands to be detected with smaller bandwidths, and detects sequentially according to the order of the frequency bands to be detected. Therefore, compared with the prior art, the present invention The solution of the embodiment to the frequency band to be detected with a smaller bandwidth can reduce the detection time and improve the detection efficiency; at the same time, the solution of the embodiment of the present invention is no longer as in the prior art-the detection unit is used every time a detection unit is detected The reference unit of the unit determines the corresponding detection threshold, but determines the detection threshold once when detecting each frequency band to be detected, and uses the determined detection threshold to detect each channel of the detection frequency band. Therefore, compared with the prior art, the solutions in the embodiments of the present invention can greatly reduce the amount of computation for calculating the detection threshold, thereby shortening the detection time. In addition, in the prior art, FFT processing is performed on the sampling data of the overall frequency range to be detected, and the influence of FFT operation points on the calculation amount increases exponentially, so too large FFT points will greatly increase the acquisition time of the system for the target signal , and in the signal detection method based on the satellite-borne antenna capture tracking pointing system provided by the embodiment of the present invention, since the overall frequency range to be detected is divided into multiple frequency bands to be detected, and the sampling data of each frequency band to be detected is channelized Processing, and then FFT processing, so the time consumption caused by FFT operation can be greatly reduced. In summary, the signal detection method based on the satellite-borne antenna acquisition tracking pointing system provided by the embodiment of the present invention can realize the detection of weak signals in a space noise environment, and the detection time is short and the detection efficiency is high.

In addition, the signal detection method based on the satellite-borne antenna acquisition tracking and pointing system provided by the embodiment of the present invention also has the outstanding advantage of high flexibility: the values of each parameter in the method of the embodiment of the present invention are variable, and can be adjusted according to the actual use process. The system requirements are adjusted, and the parameterized description makes the method of the embodiment of the present invention adaptable to various actual situations, and improves the flexibility, reusability and portability of the system design.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts.

Fig. 1 is a schematic flow diagram of a signal detection method based on a satellite-borne antenna acquisition tracking pointing system provided by an embodiment of the present invention;

Fig. 2 is a relation curve diagram of detection probability and single pulse signal-to-noise ratio;

Fig. 3 (a) is the probability density function figure of χ ² distribution;

Fig. 3 (b) is the cumulative distribution function figure of χ ² distribution;

Fig. 4 is the spectrogram of target signal;

Fig. 5 (a) is the time-domain diagram of the signal to be detected before incoherent accumulation;

Fig. 5 (b) is the spectrogram of the signal to be detected through FFT before non-coherent accumulation;

Fig. 6 is the spectrogram of the signal to be detected after non-coherent accumulation through FFT;

FIG. 7 is a diagram showing the results of detection of the signal to be detected passing the optimal detection threshold after non-coherent accumulation.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

FIG. 1 is a schematic flowchart of a signal detection method based on a satellite-borne antenna acquisition, tracking and pointing system provided by an embodiment of the present invention.

As shown in Figure 1, the signal detection method based on the satellite-borne antenna acquisition tracking pointing system provided by the embodiment of the present invention includes the following steps:

Step 1: Obtain the frequency interval to be detected and the bandwidth index value of a single frequency interval to be detected, and then divide the frequency interval to be detected into M frequency bands to be detected F ₁ , F ₂ , ... according to the bandwidth index value C of a single frequency interval to be detected , F _M , go to step 2.

in, C represents the bandwidth index value of a single frequency interval to be detected, B _F represents the bandwidth of the frequency interval to be detected, and [·] represents rounding operation.

Specifically, the frequency range to be detected can be expressed as: Among them, f ₀ represents the center frequency.

Step 2, initialization: make frequency sweep value i=1, channel number j=1, number of times of non-coherent accumulation k=1, number of times of detection n=1, number of times of detected targets p=0, set the total number of times of non-coherent accumulation K, Go to step 3.

Because in a complex space environment, the target signal is always mixed with noise and other interference, and when the target signal is relatively weak, the signal-to-noise ratio of the single sampling signal is small, and the weak signal is not easy to be detected. In the embodiment of the present invention, the signal-to-noise ratio of the signal can be improved by using non-coherent accumulation, and the detection of weak signals can be realized.

Specifically, the total number K of non-coherent accumulation can be set as:

In the formula, SNR is the minimum signal-to-noise ratio that needs to be achieved before the signal is detected and judged when the required detection performance is met, and SNR _min is the minimum signal-to-noise ratio that is required to be achieved during detection.

The basis for setting the total number of times K of non-coherent accumulation according to the above formula is given as follows:

When the detection performance required by the system is known, that is, given the detection probability P _d and the false alarm probability P _fa , according to the relationship curve between the detection probability and the signal-to-noise ratio of a single pulse, it can be known that when the required detection performance is met The minimum signal-to-noise ratio that needs to be achieved before the signal is detected and judged is assumed to be SNR. At the same time, it is known that the requirement of the system to detect the target quality is the minimum signal-to-noise ratio required to detect the signal, assuming it is SNR _min , then when the signal is incoherently accumulated, the signal-to-noise ratio that needs to be improved is SNR-SNR _min ( dB). Among them, the relationship curve between detection probability and single pulse signal-to-noise ratio is the corresponding relationship diagram between discovery probability, false alarm probability and pulse signal-to-noise ratio, and Fig. 2 shows a typical relationship between detection probability and single pulse signal-to-noise ratio In the graph, the abscissa in the figure is the signal-to-noise ratio of a single pulse, the ordinate is the detection probability, and the curve is the false alarm probability. As shown in Figure 2, when the probability of false alarm is given, the corresponding curve is constant, and under this condition, the corresponding signal-to-noise ratio can be obtained after the detection probability is given.

For non-coherent integration, when K identically distributed signals with a signal-to-noise ratio (SNR) of ₁ are integrated non-coherently, the improvement of the SNR cannot reach K times. This is because of the non-linear effect of envelope detection. When the signal plus noise passes through the detector, the interaction term between the signal and the noise will also be increased to affect the signal-to-noise ratio at the output. Especially when the signal-to-noise ratio at the detector input is low, the loss of signal-to-noise ratio at the detector output is even greater. This cumulative loss L _NCI is approximated as: The loss value is in and K, and when K is large, the cumulative loss is close to

Therefore, to achieve the required detection probability P _d under a certain false alarm probability P _fa , the SNR of K identically distributed signals with a signal-to-noise ratio of (SNR) ₁ after non-coherent accumulation is And when K is large, Then, when the signal-to-noise ratio gain of SNR-SNR _min (dB) is to be increased and the accumulation number K is relatively large, the relationship between the signal-to-noise ratio and the accumulation number K is Therefore, the required number of non-coherent accumulation is

Step 3, obtain the sampling data obtained by sampling the data of the ith frequency band F _i to be detected by the analog-to-digital converter and sample data Perform digital down-conversion processing, and then perform digital channelization processing on the sampled data after digital down-conversion processing to obtain channelized data of W channels Fast Fourier transform is performed on the channelized data of W channels respectively to obtain the spectral data of W channels Spectrum data for W channels First perform the point-by-point modulus operation, and then perform the square operation to obtain the spectral data corresponding to the kth non-coherent accumulation of W channels Go to step 4.

Among them, the spectral data of W channels Both are doped with noise N _ij , and N _ij has a Gaussian distribution, and the corresponding Gaussian sequence can be expressed as X(n) _k , n=1, 2, 3 . . .

It should be noted that, for the data of W channels When performing FFT processing, the number of FFT operation points L directly affects the amount of operation and then affects the acquisition time of the system for the target signal. When the signal sampling rate is constant, if the frequency sweep step value C is too large, the number of FFT points L will be large; if the frequency sweep step value C is too small, the channelized data would be too big. Both cases will lead to a large amount of calculation, so parameters such as the frequency sweep step value C and the number of FFT points L should be set reasonably according to the actual working conditions of the system.

Step 4, judging whether the number k of non-coherent accumulation is equal to the total number K of non-coherent accumulation; if k≠K, add 1 to k, and go to step 3; if k=K, go to step 5.

Step 5: Sum the spectral data corresponding to all K times of non-coherent accumulation of the qth channel among the W channels to obtain the decision data S _ij to be detected for the qth channel, where q takes all integer values between 1 and W ; splicing the judgment data to be detected of all W channels according to the order of the channels to obtain the overall judgment data S _i ^K to be detected of the ith frequency band F _i to be detected; using the overall judgment data to be detected of the i frequency band F _i to be detected Data S _i ^K , determine the detection threshold TH; determine the maximum value S ij max in the decision data S _ij to be detected of the jth channel, and determine the maximum value S _{ij max} in the decision data S _ij to be detected in the jth channel and the size of the detection threshold TH; if S _{ij max} >TH, go to step 6; if S _{ij max} ≤ TH, go to step 7.

Among them, the overall to-be-detected decision data S _i ^K of the i-th frequency band to be detected F _i is doped with noise It obeys the χ ² distribution, and the χ ² distribution sequence can be expressed as k=1, 2...K, n=1, 2, 3....

It should be noted that, if S _{ij max} >TH, it means that the current detection finds a potential target signal in the jth channel of the ith detection frequency band F _i . At this time, go to step 6 for execution to determine that in the current detection The signal bandwidth corresponding to the jth channel of the ith detection frequency band F _i in Conversely, if S _{ij max} ≤ TH, it means that no target signal has been detected in the jth channel of the ith detection frequency band F _i in the current detection. In order to improve the judgment accuracy and prevent misjudgment, the "P/N judgment criterion" is adopted in the embodiment of the present invention, that is, the jth channel of the i-th detection frequency band F _i is detected multiple times, and the target is detected according to the Judgment is made if the total number of detections accounts for the total number of detections. For the specific operation method, see step 7.

Preferably, if after the first detection is performed on the jth channel of the current ith detection frequency band F _i , it is found that no target signal is detected in the jth channel, then the jth channel is no longer repeatedly detected, and It is to detect the next channel directly. That is, when n=1, if it is determined in step 5 Then step 7 is no longer performed, but directly go to step 8. In this way, the detection time can be reduced so that the total detection time does not exceed the specified time required by the system.

Specifically, in step 5, the detection threshold TH is determined by using the overall undetected decision data S _i ^K of the ith frequency band F _i to be detected, which specifically includes the following steps:

(5a) Digging from the overall decision number to be detected in the i-th detection frequency band F _i Extract data points from the S _num data points to get the Q segment reference unit Wherein each reference unit includes R consecutive data points, and two adjacent reference units are separated by P consecutive data points, Calculate the average value of the data in each reference unit, obtain Q average values, determine the minimum value of the Q average values, and use the minimum value as the estimated value of the noise floor power of the i-th detection frequency band F _i

(5b) Determine the theoretical value of the noise floor power _{Na ave} , the constant false alarm detection probability P _fa , and the noise doped in the overall decision data S _i ^K to be detected in the i-th frequency band F _i to be detected cumulative distribution function F _K (Y); according to the theoretical value of noise floor power _{Na ave} , constant false alarm detection probability P _fa and cumulative distribution function F _K (Y), use the formula: P _fa =1-F _K (f×N _ave ), calculate the optimal threshold detection factor f.

Among them, the theoretical value N _ave of the noise floor power can be obtained in the following manner:

Determine the noise doped in the overall decision data S _i ^K to be detected in the i-th frequency band F _i to be detected The expected E(Y)=2K×P ₀ ×L, so that the theoretical value of the noise floor power _{Na ave} is equal to the expected E(Y).

Among them, K is the number of non-coherent accumulation, L is the number of FFT points, and P ₀ is the power of Gaussian white noise received by the radar antenna from space.

The theoretical basis for the calculation of the optimal threshold detection factor f above is given below:

Known judgment data to be detected noise doped in obeys the ^χ2 distribution and can be expressed as a sequence The probability density function of the χ2 distribution is shown in Figure ³ (a), and its expression is:

Among them, Γ() represents the Gamma function.

The cumulative distribution function of the χ2 distribution is shown in Figure ³ (b), and the functional expression of the cumulative distribution function is:

Among them, γ(Y, Z) represents the incomplete Gamma function.

From the above two equations, we can see that the noise The probability that the data in the middle is greater than the detection threshold value f×N _ave is the false alarm probability, namely: Among them, the expression of the cumulative distribution function F _K (Y) is known, then in the case of a given false alarm probability P _fa , the optimal threshold detection factor f can be obtained according to the above formula.

(5c) The estimated value of the noise floor power of the i-th detection frequency band F _i Multiply with the optimal threshold detection factor f to obtain the detection threshold TH.

It is worth noting that, in the prior art, each detection unit in the overall to-be-detected interval is detected point by point, and each time a detection unit is detected, it is necessary to obtain the corresponding The detection threshold value will undoubtedly increase the amount of computation and prolong the total detection time. However, the above-mentioned method of determining the detection threshold TH in the embodiment of the present invention is: by using the overall to-be-detected decision data from the i-th detection frequency band F _i Extract a number of reference units, and use the reference unit data to determine the estimated value of the noise floor power And use the theoretical value of the noise floor power _{Na ave} , the constant false alarm detection probability P _fa and the noise doped in the overall judgment data S _i ^K of the i-th frequency band F _i to be detected to be detected The cumulative distribution function F _K (Y) calculates the optimal threshold detection factor f, and then uses the optimal threshold detection factor f and the estimated value of the noise floor power The calculated detection threshold TH is different from the prior art. In the embodiment of the present invention, the whole interval to be detected is divided into several frequency bands to be detected. When each frequency band to be detected is detected, the detection threshold only needs to be determined once. Each channel of the detection frequency band is detected by the detection threshold. Therefore, compared with the prior art, the solutions of the embodiments of the present invention can greatly reduce the amount of computation, thereby shortening the total signal detection time.

Step 6: Add 1 to the number p of detected targets, and according to the jth channel’s decision data S _ij ^K to be detected and the maximum value of the jth channel’s decision data S _ij ^K to be detected Determine the signal bandwidth corresponding to the j-th channel of the i-th detection frequency band F _i in the n-th detection Let the signal bandwidth corresponding to the jth channel of the ith detection frequency band F _i be Go to step 7.

Specifically, in step 6, according to the decision data S _ij to be detected of the jth channel and the maximum value S _{ij max} in the decision data S _ij to be detected of the jth channel, determine the i-th detection in the n-th detection The signal bandwidth corresponding to the jth channel of the frequency band F _i include:

Taking the maximum value S _{ij max} of the decision data S _ij to be detected in the jth channel as the center, compare the left and right neighbor data of the decision data S _ij to be detected in the jth channel with the detection threshold TH, and find The left boundary point and right boundary point of TH, according to the left boundary point and the right boundary point, determine the signal bandwidth corresponding to the jth channel of the i-th detection frequency band F _i in the n-th detection

Among them, the signal bandwidth corresponding to the jth channel of the ith detection frequency band F _i in the nth detection is determined according to the left boundary point and the right boundary point Specifically: determine the number of data points between the left boundary point and the right boundary point (including the left boundary point and the right boundary point), multiply the number of data points by the resolution, and obtain the i-th detection frequency band F _i in the n-th detection The signal bandwidth corresponding to the jth channel of

Step 7: Add 1 to the number of detections n, and determine whether the number of detections n is less than or equal to the preset number of detections N; if the number of detections n is less than or equal to the number of preset detections N, go to step 3; if the number of detections n is greater than the number of preset detections N, then judge whether the number p of detected targets is greater than the preset value P; if p≤P, then determine that no target signal has been detected in the jth channel of the i-th frequency band F _i to be detected, so that the i-th detection The signal bandwidth B _ij corresponding to the jth channel of the frequency band F _i = 0, go to step 8; otherwise, if p>P, it is determined that the target signal is detected in the jth channel of the ith frequency band F _i to be detected , go to step 8.

Step 8: Add 1 to the channel number j, and judge whether j is equal to the total number of channels W; if j=W, go to step 5; otherwise, go to step 9.

Step 9, determine whether a signal is detected in the W channels of the _i -th frequency band F to be detected; if no target signal is detected in the W channels of the _i -th frequency band F to be detected, then the frequency sweep value Add 1 to i, and go to step 3; if the target signal is detected in w channels among the W channels of the i-th frequency band F _i to be detected, go to step 10.

Wherein, w is an integer, 1≤w≤W.

Step 10, using the signal bandwidth corresponding to each of the w channels, the bandwidth B _F of the frequency interval to be detected, the number of channels W, and the number of frequency bands to be detected M, to determine the target signal bandwidth B _i .

Specifically, step 10 may specifically include the following steps:

(10a) According to the signal bandwidth corresponding to each channel in the w channels, determine the maximum signal bandwidth B _{ij max} and the channel j _max where the maximum signal bandwidth B _{ij max} is located; judge the maximum signal bandwidth B _{ij max} and the bandwidth of a single channel is equal; if Determine the target signal bandwidth Bi=B _{ij max} ; otherwise, go to step 10b.

(10b) Take the channel j _max as the center point to judge the left channel j _L and the right channel j _R respectively, so as to determine the total bandwidth of the left channel respectively and the total bandwidth of the right channel According to the total bandwidth of the left channel Total right channel bandwidth And the maximum signal bandwidth B _{ij max} to determine the target signal bandwidth

Wherein, 0<j _L <j _max , j _max <j _R ≤ W.

Specifically, judge the left channel j _L to determine the total bandwidth of the left channel Specifically, the following steps may be included:

(10b11) Let j _L = j _max -1, the total bandwidth of the left channel

(10b12) Determine the bandwidth of the left channel j _L with the bandwidth of a single channel is equal; if Let the total bandwidth of the left channel like Let the total bandwidth of the left channel Subtract 1 from j _L and go to step 10b13.

(10b13) Determine whether j _L is equal to 1; if j _L ≠1, then go to step 10b12; if j _L =1, output the total bandwidth of the left channel

Similarly, judge the right channel j _R to determine the total bandwidth of the left channel Specifically, the following steps may be included:

(10b21) Let j _R =j _max +1, the total bandwidth of the right channel

(10b22) Determine the bandwidth of the right channel j _R with the bandwidth of a single channel is equal; if Then determine the total bandwidth of the right channel like Let the total bandwidth of the right channel Subtract 1 from j _R and go to step 10b23.

(10b23) Judging whether j _R is equal to W; if j _R ≠ W, then go to step 10b12; if j _R = W, output the total bandwidth of the right channel

So far, a detection of the entire frequency range to be detected has been completed. If a target signal is detected in this detection, the corresponding target signal bandwidth will be output for the system to use the target signal bandwidth to extract information such as azimuth difference and pitch difference of the target. , to realize the error correction of the antenna pointing to the target.

Based on the signal detection method based on the satellite-borne antenna acquisition tracking pointing system provided by the above-mentioned embodiments of the present invention, on the one hand, due to the use of non-coherent accumulation to improve the signal-to-noise ratio, compared with coherent accumulation, the embodiment of the present invention adopts The engineering implementation of non-coherent accumulation is relatively simple, and the amount of calculation is relatively small, and for fast-fluctuating received signals, non-coherent accumulation will also obtain better detection results. Therefore, the embodiment of the present invention provides The signal detection method of the tracking and pointing system can realize the detection of weak signals in the space noise environment. On the other hand, the existing technology adopts the scheme of detecting the whole to-be-detected interval, and the data in the entire to-be-detected interval needs to be processed during the detection. Due to the large amount of data, it will take a long time to read/write data , so that the detection time is longer and the detection efficiency is lower; and different from the prior art, the signal detection method based on the satellite-borne antenna capture tracking and pointing system provided by the embodiment of the present invention does not use the overall detection method in the prior art Instead, the overall interval to be detected is divided into several frequency bands to be detected with smaller bandwidths, and the frequency bands to be detected are sequentially detected. The scheme of the frequency band to be detected can greatly shorten the time taken for data reading and writing, thereby reducing the detection time and improving the detection efficiency. At the same time, the solution of the embodiment of the present invention is no longer as in the prior art—when each detection unit is detected, the reference unit of the detection unit is used to determine the corresponding detection threshold. Instead, each frequency band to be detected is detected The detection threshold is determined once every time, and each channel of the detection frequency band is detected by using the determined detection threshold. Therefore, compared with the prior art, the solutions in the embodiments of the present invention can greatly reduce the amount of computation for calculating the detection threshold, thereby shortening the detection time. In addition, in the prior art, FFT processing is performed on the sampling data of the overall frequency range to be detected, and the influence of FFT operation points on the calculation amount increases exponentially, so too large FFT points will greatly increase the acquisition time of the system for the target signal , and in the signal detection method based on the satellite-borne antenna capture tracking pointing system provided by the embodiment of the present invention, since the overall frequency range to be detected is divided into multiple frequency bands to be detected, and the sampling data of each frequency band to be detected is channelized Processing, and then FFT processing, so the time consumption caused by FFT operation can be greatly reduced. In summary, the signal detection method based on the satellite-borne antenna acquisition tracking pointing system provided by the embodiment of the present invention can realize the detection of weak signals in a space noise environment, and the detection time is short and the detection efficiency is high.

In addition, the signal detection method based on the satellite-borne antenna acquisition tracking and pointing system provided by the embodiment of the present invention also has the outstanding advantage of high flexibility: the values of each parameter in the method of the embodiment of the present invention are variable, and can be adjusted according to the actual use process. The system requirements are adjusted, and the parameterized description makes the method of the embodiment of the present invention adaptable to various actual situations, and improves the flexibility, reusability and portability of the system design.

The effect of the signal detection method based on the satellite-borne antenna capture tracking pointing system provided by the embodiment of the present invention is further illustrated through simulation experiments as follows:

1. Simulation conditions:

In order to focus on the detection of the target signal by the system, this simulation experiment only conducts experiments on one channel. The target signal is set as a random uniformly distributed signal with a bandwidth of 2MHz, the sampling rate f _s =18.75MHz, and the target signal is submerged under the noise background by adding a certain power of noise, and the signal-to-noise ratio within the bandwidth is fixed at SNR=5dB.

2. Simulation experiment content:

① Use a random function to generate a random uniformly distributed target signal with a given bandwidth, and add a certain amount of noise according to the signal-to-noise ratio (SNR) within the bandwidth. The noise is randomly generated, and the channel signal to be detected is obtained, and the power spectrum of the signal to be detected is drawn.

②According to the system algorithm, the channel signal to be detected is sampled through the sampling frequency f _s , and then the sampled signal is subjected to FFT transformation, modulo operation, square operation, and accumulation operation.

_{③According to the signal-to-noise ratio SNR within a given bandwidth and the given discovery probability Pd and false alarm rate Pfa ,} determine the number of non-coherent accumulation K, and then complete the non-coherent accumulation of the channel signal to be detected for the process ② loop K times, And draw the power spectrum of the signal to be detected after incoherent accumulation.

4. according to the determination method of optimum threshold detection factor f in the method of the embodiment of the present invention, utilize process 3. the result of incoherent accumulation obeys the characteristic and system performance of χ2 distribution to determine optimum threshold detection factor ^f ; In conjunction with this emulation, process 3. The result of non-coherent accumulation takes 3 reference units at equal intervals, and the number of data points in each reference unit is 500 points, and the minimum value of the average value of the 3 reference units is used as the estimated value of the noise floor power of the channel signal to be detected, thus determining Optimal detection threshold.

5. According to the method of the embodiment of the present invention, the optimal detection threshold of the process 4. is used to detect the channel signal to be detected after the process 3. non-coherent accumulation; if a potential target signal is detected, in order to avoid the impact of false alarms on the detection performance of the system, use "P/N Judgment Criterion", combined with this simulation, repeat N=5 times of detection, if the number of detected target signals P≥3, it means that the target signal is detected, otherwise the detected potential target signal is generated by a false alarm, Draw a graph of the signal detection results.

3. Simulation result analysis:

Figure 4 shows the frequency spectrum of the target signal in the simulation test. Looking at Figure 4, it can be seen that the target signal is a uniformly distributed signal with a bandwidth of B=2MHz, and the spectral height within the signal bandwidth is relatively large, while the spectral height of signals at other positions is very small.

Fig. 5(a) shows the time-domain diagram of the signal to be detected before non-coherent integration, and Fig. 5(b) shows the frequency spectrum of the signal to be detected before non-coherent integration after FFT. Observing Figures 5(a) and 5(b), it can be seen that without incoherent accumulation of the signal to be detected, the target signal is basically submerged in noise and cannot be detected.

FIG. 6 shows a frequency spectrum diagram of the signal to be detected after non-coherent accumulation through FFT. Observing Figure 6, it can be seen that the signal-to-noise ratio of the signal has been greatly improved after non-coherent accumulation.

Fig. 7 is a diagram showing the results of detection of the signal to be detected passing the optimal detection threshold after non-coherent accumulation. Observing Figure 7, it can be seen that the target signal has been detected, and the signal-to-noise ratio of the target signal is large.

Those of ordinary skill in the art can understand that all or part of the steps for realizing the above-mentioned method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the It includes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other various media that can store program codes.

The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Anyone skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present invention. Should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (8)

1. a signal detection method based on satellite-borne antenna capture tracking pointing system, is characterized in that, described method comprises the following steps: Step 1, obtaining the frequency interval to be detected and the bandwidth index value of a single frequency interval to be detected, and then dividing the frequency interval to be detected into M frequency bands F1 to be detected according to the bandwidth index value C _of the single frequency interval to be detected, F ₂ ,…,F _M , go to step 2; where, C represents the bandwidth index value of a single frequency range to be detected, B _F represents the bandwidth of the frequency range to be detected, and [ ] represents rounding operation; Step 2, initialization: make frequency sweep value i=1, channel number j=1, number of times of non-coherent accumulation k=1, number of times of detection n=1, number of times of detected targets p=0, set the total number of times of non-coherent accumulation K, Go to step 3; Step 3, obtain the sampling data obtained by sampling the data of the ith frequency band F _i to be detected by the analog-to-digital converter and for the sampled data Perform digital down-conversion processing, and then perform digital channelization processing on the sampled data after digital down-conversion processing to obtain channelized data of W channels Fast Fourier transform is performed on the channelized data of the W channels respectively to obtain the spectrum data of the W channels For the spectral data of the W channels Carry out the point-by-point modulus calculation first, and then perform the square operation to obtain the spectral data corresponding to the kth non-coherent accumulation of the W channels Go to step 4; Step 4, judging whether the number k of non-coherent accumulation is equal to the total number K of non-coherent accumulation; if k≠K, add 1 to k, and go to step 3; if k=K, go to step 5; Step 5: Summing the spectral data corresponding to all K times of non-coherent accumulation of the qth channel in the W channels to obtain the decision data S _ij to be detected for the qth channel, where q ranges from 1 to W All integer values between ; Splicing the judgment data to be detected of all W channels according to the order of the channels to obtain the overall judgment data S _i ^K to be detected of the ith frequency band F _i to be detected; Using the overall _undetected decision data S _i ^K of the _ith frequency band F _i to be detected, determine the detection threshold TH; The maximum value S _ijmax of the decision data S _ij to be detected for j channels and the size of the detection threshold TH; if S _ijmax > TH, go to step 6; if S _{ijmax ≤} TH, go to step 7; Step 6: Add 1 to the number p of detected targets, and determine according to the maximum value S _ijmax of the decision data S _ij to be detected in the jth channel and the decision data S _ij to be detected in the jth channel The signal bandwidth corresponding to the j-th channel of the i-th detection frequency band F _i in the n-th detection Make the signal bandwidth corresponding to the jth channel of the ith detection frequency band F _i Go to step 7; Step 7, adding 1 to the number of detection times n, and judging whether the number of detection times n is less than or equal to the preset number of detection times N; If the detection times n is less than or equal to the preset detection times N, go to step 3; If the number of detections _n is greater than the preset number of detections N, it is judged whether the number of times p of the detected target is greater than the preset value P; If no target signal is detected in the channel, set the signal bandwidth B _ij corresponding to the jth channel of the i-th detection frequency band F _i =0, and go to step 8; otherwise, if p>P, then determine that If the target signal is detected in the jth channel of the i frequency band F _i to be detected, go to step 8; Step 8, add 1 to the channel number j, and judge whether j is equal to the total number of channels W; if j=W, go to step 9, otherwise, go to step 5; Step 9, determining whether a signal is detected in the W channels of the _i -th frequency band F to be detected; if no target signal is detected in the W channels of the _i -th frequency band F to be detected, then Add 1 to the frequency sweep value i, and go to step 3; if a target signal is detected in w channels among the W channels of the _i -th frequency band F to be detected, go to step 10; wherein, w is an integer , 1≤w≤W; Step 10, using the signal bandwidth corresponding to each of the w channels, the bandwidth B _F of the frequency interval to be detected, the number of channels W, and the number of frequency bands to be detected M, to determine the target signal bandwidth B _i . 2. The method according to claim 1, wherein in step 5, the determination of the detection threshold TH using the overall decision data S _i ^K to be detected of the ith frequency band F _i to be detected, specifically includes the following step: (5a) From the overall to-be-detected decision data of the i-th detection frequency band F _i Extract data points from the S _num data points to get the Q segment reference unit Wherein each reference unit includes R consecutive data points, and two adjacent reference units are separated by P consecutive data points, Find the average value of the data in each section of the reference unit, obtain Q average values, determine the minimum value in the Q average values, and use the minimum value as the noise floor power estimate value of the ith detection frequency band F _i (5b) Determine the theoretical value of the noise floor power _{Na ave} , the constant false alarm detection probability P _fa , and the noise doped in the overall decision data S _i ^K to be detected of the i-th frequency band F _i to be detected The cumulative distribution function F _K (Y); According to the theoretical value of the noise floor power _{Na ave} , the constant false alarm detection probability P _fa and the cumulative distribution function F _K (Y), use the formula: P _fa =1-F _K (f×N _ave ) to calculate Get the best threshold detection factor f; (5c) the estimated value of the noise floor power of the i-th detection frequency band F _i Multiply with the optimal threshold detection factor f to obtain the detection threshold TH. 3. method according to claim 2, is characterized in that, described determining noise floor power theoretical value N _ave comprises: Determining the noise doped in the overall decision data S _i ^K to be detected of the ith frequency band F _i to be detected The expected E(Y)=2K×P ₀ ×L, so that the theoretical value of the noise floor power _{Na ave} is equal to the expected E(Y); where K is the number of non-coherent accumulations, L is the number of FFT points, and P ₀ is the radar antenna The power of white Gaussian noise received from the space. 4. The method according to any one of claims 1-3, characterized in that, in step 6, the decision data S _ij to be detected according to the jth channel and the to-be-detected data S ij of the jth channel Determine the maximum value S _ijmax in the judgment data S _ij , and determine the signal bandwidth corresponding to the jth channel of the i-th detection frequency band F _i in the n-th detection include: Taking the maximum value S _ijmax of the decision data S _ij to be detected in the jth channel as the center, comparing the left and right neighbor data of the decision data S _ij to be detected in the jth channel with the detection threshold TH , finding a left boundary point and a right boundary point smaller than the detection threshold TH, and determining the jth of the ith detection frequency band F _i in the nth detection according to the left boundary point and the right boundary point The signal bandwidth corresponding to the channel 5. The method according to claim 4, wherein step 10 specifically comprises the following steps: (10a) According to the signal bandwidth corresponding to each channel in the w channels, determine the maximum signal bandwidth B _ijmax and the channel j _max where the maximum signal bandwidth B _ijmax is located; Judging the maximum signal bandwidth B _ijmax and the bandwidth of a single channel is equal; if Determine the target signal bandwidth B _i =B _ijmax ; otherwise, go to step 10b; (10b) Take the channel j _max as the center point to judge the left channel j _L and the right channel j _R respectively, so as to determine the total bandwidth of the left channel respectively and the total bandwidth of the right channel Among them, 0<j _L <j _max , j _max <j _R ≤ W; According to the total bandwidth of the left channel The total bandwidth of the right channel and the maximum signal bandwidth B _ijmax , determine the target signal bandwidth 6. The method according to claim 4, characterized in that, the left channel j _L is judged to determine the total bandwidth of the left channel Specifically include the following steps: (10b11) Let j _L = j _max -1, the total bandwidth of the left channel (10b12) Determine the bandwidth of the left channel j _L with the bandwidth of a single channel is equal; if Let the total bandwidth of the left channel like Let the total bandwidth of the left channel Subtract 1 from j _L , go to step 10b13; (10b13) Determine whether j _L is equal to 1; if j _L ≠1, then go to step 10b12; if j _L =1, output the total bandwidth of the left channel 7. The method according to claim 4, characterized in that, the right channel j _R is judged to determine the total bandwidth of the left channel Specifically include the following steps: (10b21) Let j _R =j _max +1, the total bandwidth of the right channel (10b22) Determine the bandwidth of the right channel j _R with the bandwidth of a single channel is equal; if Then determine the total bandwidth of the right channel like Let the total bandwidth of the right channel Subtract 1 from j _R , go to step 10b23; (10b23) Judging whether j _R is equal to W; if j _R ≠ W, then go to step 10b12; if j _R = W, output the total bandwidth of the right channel 8. The method according to claim 7, wherein the total number of times of non-coherent accumulation Among them, SNR is the minimum signal-to-noise ratio that needs to be achieved before the signal is detected and judged when the required detection performance is met, and SNR _min is the minimum signal-to-noise ratio that is required to be achieved during detection.