Moving target Doppler compensation coherent detection method based on single vector hydrophone

Abstract

The invention provides a moving target Doppler compensation coherent detection method and system based on a single-vector hydrophone, and the method comprises the steps: S1, collecting a receiving signal of the single-vector hydrophone, and carrying out the segmentation of the receiving signal, and obtaining segmented data; s2, estimating a scale factor of the received data of the current segment according to the segmented data; s3, compensating the corresponding segmented data according to the scale factor to obtain a compensated signal; and S4, performing coherent accumulation processing on the compensated signal to obtain a sound intensity detection result, namely signal-to-noise ratio gain. The scale factor is a Doppler coefficient. Based on the improvement of a conventional sound pressure Doppler compensation method, in view of the advantages of the vector hydrophone, a new moving target Doppler compensation coherent detection method based on the single vector hydrophone is provided, and the detection performance of the single vector hydrophone on the moving target is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of moving target detection, and in particular relates to a moving target Doppler compensation coherent detection method based on a single vector hydrophone. Background Art

[0002] Due to the high speed of targets such as surface ships, there are more line spectrum components in the radiated noise, and the energy and frequency of the line spectrum are more concentrated and stable than the broadband spectrum. In addition, the characteristics of the line spectrum can further realize the recognition and classification of the target. The feature extraction of the line spectrum in the radiated noise of fast-moving targets has always been a hot research issue in the field of passive sonar signal processing for underwater acoustic countermeasures. However, it is affected by the Doppler effect when moving, which will cause the passive sonar receiving signal to be unstable and have time-varying characteristics, especially when the target is changing speed or turning.

[0003] At present, most of the commonly used passive target detection methods are based on the assumption that the received signal is a stationary signal. When processing the non-stationary signal of the noise radiated by the moving target, the data that can be coherently accumulated is short or cannot be coherently accumulated, thereby reducing the signal-to-noise ratio gain that can be provided by coherent accumulation, resulting in a significant decrease in detection performance. If long-term coherent accumulation is forced, it will cause problems such as target line spectrum frequency offset and spectrum peak broadening in the output result, affecting subsequent detection performance.

[0004] Therefore, it is of great significance to study the long-term coherent detection technology suitable for moving targets, overcome the influence of Doppler effect on line spectrum estimation, and effectively increase the time length of integration processing.

[0005] In recent years, researchers have continuously studied and improved the Doppler compensation method for moving target signals in response to the above-mentioned problems. At present, the commonly used method is based on dual acoustic pressure hydrophones to simultaneously compensate for the Doppler coefficient and delay difference of the dual-channel mutual power spectrum of the received signal. It is necessary to decouple the two and then perform coherent accumulation. However, the single accumulation process of the above operation is complex and time-consuming, which cannot meet the real-time requirements for moving target detection and is difficult to apply in actual engineering. Therefore, it is necessary to study a moving target Doppler compensation algorithm with higher real-time performance and better performance.

[0006] The vector hydrophone itself can obtain additional spatial gain by utilizing the dipole directivity of the velocity component of the sensor, and can output higher-performance detection quantities for extracting the target radiation noise line spectrum, and the sound pressure of the signal received by the vector hydrophone is consistent with the velocity phase. The above characteristics provide the possibility of improving the Doppler compensation mechanism of the conventional dual-acoustic pressure hydrophone.

[0007] Patent document CN102916922A discloses an underwater acoustic OFDM adaptive search Doppler compensation method, the purpose of which is to provide an underwater acoustic OFDM adaptive search Doppler compensation method, using CW signal as a training sequence to roughly measure the Doppler frequency deviation factor. The scheme uses high-power DFT to compensate for the Doppler frequency deviation, uses the Doppler frequency deviation factor measured by the CW signal as the initial value, and uses the mean square error of the compensated and equalized data as the cost function, and continuously adjusts the factor size for searching until the conditions are met. The present invention overcomes the disadvantage that the Doppler frequency deviation factor measured by the existing block Doppler estimation or single-frequency signal frequency measurement method has a certain error, and also overcomes the disadvantage that if the measured factor is directly used for Doppler frequency deviation compensation, it will cause the data constellation diagram to diverge, that is, the increase of the mean square error of the data. However, the scheme needs to perform decoupling calculation of the Doppler coefficient and the delay difference in order to complete the Doppler compensation, and does not solve the problem of real-time performance.

[0008] This problem needs to be solved urgently. Summary of the invention

[0009] In view of the defects in the prior art, an object of the present invention is to provide a moving target Doppler compensated coherent detection method based on a single vector hydrophone.

[0010] According to the present invention, a moving target Doppler compensation coherent detection method based on a single vector hydrophone includes: step S1: collecting a received signal of the single vector hydrophone, segmenting it, and obtaining segmented data;

[0011] Step S2: estimating the scale factor of the received data of the current segment according to the segmented data;

[0012] Step S3: compensating the corresponding segmented data according to the scale factor to obtain a compensated signal;

[0013] Step S4: coherently add and process the compensated signal to obtain a sound intensity detection result, namely, a signal-to-noise ratio gain.

[0014] The scale factor is the Doppler coefficient.

[0015] Preferably, the step S1 includes:

[0016] Step S1.1: collecting the received signal of a single vector hydrophone;

[0017] Step S1.2: Divide the received signal into M segments to obtain segmented data;

[0018] In the step S2, it includes:

[0019] Step S2.1: Setting the search range of the scale factor;

[0020] Step S2.2: According to the search range, traverse the scale factor, resample the segmented data of the first (M-1) segments, estimate the received signal corresponding to the scale factor, and obtain an evaluation result;

[0021] In step S2.1, the search range of the scale factor is expressed mathematically as follows:

[0022]

[0023] Among them, α max Indicates the maximum value of the scale factor; α min Indicates the minimum value of the scale factor; v max is the maximum speed of the target to be detected, c is the underwater sound speed;

[0024] In step S2.2, the evaluation result is expressed mathematically as follows:

[0025] p i (t / α i ), i=1,2,…,(M-1) (3)

[0026] Among them, p i (t / α i ) represents a received signal as an evaluation result;

[0027] The evaluation result and the sound pressure signal are respectively subjected to Fourier transform to obtain the evaluation result modulus value, i.e. |α i P i (αω)| and the modulus of the sound pressure signal, that is, |P M (ω)|.

[0028] Preferably, in step S3, a correlation coefficient is calculated according to the evaluation result of the scale factor, and the sound pressure and vibration velocity signals of the received signal are compensated based on the correlation coefficient to obtain a compensated result;

[0029] The mathematical expression of the correlation coefficient is:

[0030]

[0031] Among them, w(α i ) represents the correlation coefficient; Cov represents the covariance; D represents the variance; where |P i (α i ω)| is the amplitude spectrum of the i-th segment sound pressure receiving signal after stretching or compression in the time domain, obtained based on the evaluation result modulus;

[0032] The scale factor corresponding to the maximum value of the correlation coefficient is expressed as follows:

[0033]

[0034] Among them, arg represents the value of the independent variable when the expression reaches the maximum or minimum value; Represents traversal α i Make the expression value maximum;

[0035] The mathematical expression of the result after compensation is:

[0036]

[0037] in, Represents the compensated sound pressure channel signal; Represents the compensated vibration velocity x-direction channel signal; Represents the compensated vibration velocity y-direction channel signal.

[0038] Preferably, the step S4 includes:

[0039] Step S4.1: Fourier transform the compensated result to obtain a corresponding spectrum;

[0040] Step S4.2: according to the frequency spectrum, obtaining the sound intensity of each segment after motion compensation;

[0041] Step S4.3: coherently accumulate and process the sound intensity sequences after compensation in each segment to obtain the sound intensity detection results;

[0042] In step S4.2, the spectrum includes P i (ω), VX i (ω) and VY i (ω), the corresponding sound intensity, mathematical expression is:

[0043]

[0044] Among them, IX i (ω) represents the sound intensity in the x direction after Doppler compensation; IY i (ω) represents the sound intensity in the y direction after Doppler compensation; I i (ω) represents the total sound intensity after Doppler compensation; Re represents the real part operation; the symbol “·” represents the dot multiplication operation; the superscript * represents the conjugate operation;

[0045] In step S4.3, the sound intensity detection result is expressed mathematically as follows:

[0046]

[0047] Among them, I CPS (ω) represents the sound intensity detection result; M represents the number of segments.

[0048] According to the present invention, a moving target Doppler compensation coherent detection system based on a single vector hydrophone includes: a module M1: collecting a received signal of the single vector hydrophone, segmenting it, and obtaining segmented data;

[0049] Module M2: estimating the scale factor of the received data of the current segment according to the segmented data;

[0050] Module M3: compensating the corresponding segmented data according to the scale factor to obtain a compensated signal;

[0051] Module M4: coherently accumulates and processes the compensated signal to obtain a sound intensity detection result, that is, a signal-to-noise ratio gain.

[0052] The scale factor is the Doppler coefficient.

[0053] Preferably, the module M1 includes:

[0054] Module M1.1: Collect the received signal of a single vector hydrophone;

[0055] Module M1.2: Divide the received signal into M segments to obtain segmented data;

[0056] The module M2 includes:

[0057] Module M2.1: Set the search range of the scale factor;

[0058] Module M2.2: according to the search range, traverse the scale factor, resample the segmented data of the first (M-1) segments, estimate the received signal corresponding to the scale factor, and obtain an evaluation result;

[0059] In the module M2.1, the search range of the scale factor is expressed as follows:

[0060]

[0061] Among them, α max Indicates the maximum value of the scale factor; α min Indicates the minimum value of the scale factor; v max is the maximum speed of the target to be detected, c is the underwater sound speed;

[0062] In the module M2.2, the evaluation result is expressed mathematically as follows:

[0063] p i (t / α i ), i=1,2,…,(M-1) (3)

[0064] Among them, p i (t / α i) represents a received signal as an evaluation result;

[0065] The evaluation result and the sound pressure signal are respectively subjected to Fourier transform to obtain the evaluation result modulus value, i.e. |α i P i (αω)| and the modulus of the sound pressure signal, that is, |P M (ω)|.

[0066] Preferably, in the module M3, a correlation coefficient is calculated according to the evaluation result of the scale factor, and the sound pressure and vibration velocity signals of the received signal are compensated based on the correlation coefficient to obtain a compensated result;

[0067] The mathematical expression of the correlation coefficient is:

[0068]

[0069] Among them, w(α i ) represents the correlation coefficient; Cov represents the covariance; D represents the variance; where |P i (α i ω)| is the amplitude spectrum of the i-th segment sound pressure receiving signal after stretching or compression in the time domain, obtained based on the evaluation result modulus;

[0070] The scale factor corresponding to the maximum value of the correlation coefficient is expressed as follows:

[0071]

[0072] Among them, arg represents the value of the independent variable when the expression reaches the maximum or minimum value; Represents traversal α i Make the expression value maximum;

[0073] The mathematical expression of the result after compensation is:

[0074]

[0075] in, Represents the compensated sound pressure channel signal; Represents the compensated vibration velocity x-direction channel signal; Represents the compensated vibration velocity y-direction channel signal.

[0076] Preferably, the module M4 includes:

[0077] Module M4.1: Fourier transform the compensated result to obtain the corresponding spectrum;

[0078] Module M4.2: deriving the sound intensity of each segment after motion compensation according to the frequency spectrum;

[0079] Module M4.3: Coherently accumulate and process the sound intensity sequence after compensation in each segment to obtain the sound intensity detection result;

[0080] In the module M4.2, the spectrum includes P i (ω), VX i (ω) and VY i (ω), the corresponding sound intensity, mathematical expression is:

[0081]

[0082] Among them, IX i (ω) represents the sound intensity in the x direction after Doppler compensation; IY i (ω) represents the sound intensity in the y direction after Doppler compensation; I i (ω) represents the total sound intensity after Doppler compensation; Re represents the real part operation; the symbol “·” represents the dot multiplication operation; the superscript * represents the conjugate operation;

[0083] In the module M4.3, the sound intensity detection result is expressed as follows:

[0084]

[0085] Among them, I CPS (ω) represents the sound intensity detection result; M represents the number of segments.

[0086] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the moving target Doppler compensation coherent detection method based on a single vector hydrophone are implemented.

[0087] An electronic device provided according to the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the moving target Doppler compensation coherent detection method based on a single vector hydrophone are implemented.

[0088] Compared with the prior art, the present invention has the following beneficial effects:

[0089] 1. Aiming at the problem that the moving target detection process is easily affected by the Doppler effect and more processing gain cannot be obtained through long-term coherent accumulation, the present invention is based on improving the conventional sound pressure Doppler compensation method. In view of the advantages of vector hydrophones, a new moving target Doppler compensation coherent detection method based on a single vector hydrophone is provided to improve the detection performance of the single vector hydrophone for moving targets.

[0090] 2. Compared with the traditional target signal coherent accumulation detection method without Doppler compensation, the compensated sound intensity spectrum coherent accumulation method of the present invention can correct the frequency deviation and phase change caused by the target movement. The scale factor used for compensation is estimated according to the movement of the target, which is suitable for the situation where the target changes speed or turns, so it can achieve long-term coherent accumulation. Under ideal conditions, the accumulation gain that can be obtained by coherent accumulation using the compensated sound intensity spectrum is 10lg(M), and the accumulation gain is proportional to the accumulation number M, thereby effectively improving the detection gain of moving targets.

[0091] 3. Compared with the commonly used dual-acoustic pressure hydrophone signal cross-spectrum Doppler compensation technology, the present invention adopts a cross-spectrum sound intensity Doppler compensation enhanced detection mechanism based on vector hydrophones, and takes advantage of the fact that the vector hydrophones synchronously pick up the sound pressure and velocity signals at the same point in phase. Doppler compensation can be completed without decoupling calculation of Doppler coefficient and time delay difference, and long-term coherent accumulation can be achieved, thereby improving the real-time performance of the detection algorithm and being better suitable for practical application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0093] Figure 1 A schematic diagram of the algorithm processing flow provided by the present invention;

[0094] Figure 2 A target motion trajectory diagram set during the simulation verification provided by the present invention;

[0095] Figure 3 This is a diagram of signal detection results when the simulation target provided by the present invention is stationary, wherein: Figure 3 (a) is the time domain waveform of the received signal when the target is stationary. Figure 3 (b) is the frequency domain sound intensity diagram of the received signal when the target is stationary;

[0096] Figure 4 This is a diagram of the signal intensity detection result when the simulated target moves provided by the present invention, wherein: Figure 4 (a) is the result of 20s unsegmented direct detection, where Figure 4 (b) is the result of 20s segmented coherent accumulation detection;

[0097] Figure 5 The scale factor search process and result diagram in the simulation verification provided by the present invention, wherein: Figure 5 (a) is the scale factor search process for each segmented data. Figure 5 (b) is the result of time series measurement of scale factor;

[0098] Figure 6 A diagram showing the detection results of the signal sound intensity after Doppler compensation when the simulated target moves provided by the present invention;

[0099] Figure 7 A GPS positioning trajectory diagram of a yacht target in the lake test verification provided by the present invention;

[0100] Figure 8 The scale factor search process and result diagram for the lake test verification provided by the present invention, wherein: Figure 5 (a) is the scale factor search process for each segmented data. Figure 5 (b) is the result of time series measurement of scale factor;

[0101] Fig. 9 The present invention provides a comparison chart of the signal intensity detection results before and after Doppler compensation of the lake test data in the frequency band of 100Hz-5000Hz, wherein: Fig. 9 (a) is the detection result before Doppler compensation. Fig. 9 (b) is the detection result after Doppler compensation;

[0102] Fig.10 The present invention provides Fig. 9 A local zoomed display on the frequency axis. DETAILED DESCRIPTION

[0103] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0104] The present invention relates to a method for long-term coherent accumulation detection and direction finding of a moving target based on a single vector hydrophone. The method particularly utilizes the advantage of the common-point synchronous pickup of sound pressure and vibration velocity signals by the vector hydrophone in phase consistency to perform fast and effective cross-spectrum sound intensity Doppler compensation. After the compensation, a higher signal-to-noise ratio gain can still be obtained by increasing the processing time when the target is moving, thereby improving the line spectrum detection capability of the single vector hydrophone for the moving target.

[0105] Aiming at the shortcomings of the existing algorithms, a moving target Doppler compensation coherent detection method based on a single vector hydrophone is invented. The method mainly includes two parts: cross-spectrum Doppler compensation based on vector hydrophone and long-term coherent accumulation detection.

[0106] The algorithm can combine the advantages of vector hydrophone and Doppler compensation processing gain to improve the detection performance of vector hydrophone for moving targets. The specific implementation includes the following steps, including:

[0107] (1) Cross-spectrum Doppler compensation based on vector hydrophone

[0108] The vector hydrophone can synchronously pick up the sound pressure and velocity signals of the sound source at the same point. In the far-field conditions of the ocean waveguide, except for very low frequency sound waves, the sound pressure and velocity of the coherent sound source are roughly in phase, and their normalized correlation coefficient is close to 1. Therefore, a single vector hydrophone can be used to obtain three phase-consistent signals p(t), vx(t), and vy(t). Regardless of whether the sound source moves or not, the phase of the cross-power spectrum of p(t) and vx(t) and the cross-power spectrum of p(t) and vy(t) will always remain consistent, eliminating the influence of the delay difference in the Doppler compensation algorithm of the traditional dual-acoustic pressure hydrophone, that is, when the target moves, the amplitude and phase of the cross-power spectrum of the signal received by the vector hydrophone will only be affected by the Doppler coefficient.

[0109] On the basis of the above theoretical derivation, the present invention selects the received signal within a certain time range of any channel of the vector hydrophone, segments it in the time domain, and assumes that the Doppler coefficient in each segment of data is a constant, estimates the Doppler coefficient of each segment of data relative to the current segment of received data, that is, the scale factor, and then compensates the Doppler coefficient to the corresponding segment of sound pressure and velocity data to correct the frequency offset of the sound source signal. After compensation, the cross-power spectrum of the sound pressure and velocity of the sound source signal of all data segments will have the same frequency and phase, so as to realize the long-term coherent accumulation of the sound intensity spectrum of the vector hydrophone and significantly improve the signal-to-noise ratio, and improve the line spectrum detection capability of the moving target.

[0110] In order to estimate the Doppler coefficient, first, we need to select a vector hydrophone receiving signal such as p(t) and divide it into M segments. Due to the motion of the target, the first (M-1) segment is stretched or expanded to a certain extent in the time domain compared with the last segment. The scale factor α is used to calculate the Doppler coefficient. i Indicates that the search range of the scale factor is calculated by the receiver processing signal frequency band and the maximum speed of the target to be detected:

[0111] α i ∈[α min , α max ] (1)

[0112] Among them, α i represents the scale factor, α represents the preset list of scale factors to be searched; α min Indicates the minimum value of the scale factor; α max Indicates the maximum value of the scale factor;

[0113]

[0114] Among them, α max Indicates the maximum value of the scale factor; α minIndicates the minimum value of the scale factor; v max is the maximum speed of the target to be detected, and c is the underwater sound speed.

[0115] Then, we traverse the scale factors and resample the first (M-1) segments to obtain the received signal corresponding to each possible value of the scale factor:

[0116] p i (t / α i ), i=1,2,…,(M-1) (3)

[0117] Among them, p i (t / α i ) represents a received signal as an evaluation result;

[0118] Then for p i (t / α i ) and the last segment of the sound pressure signal p M (t) respectively perform Fourier transform and take the modulus value to obtain |α i P i (αω)| and |P M (ω)|, then |α i P i (αω)|divided by α on the magnitude i Get|P i (α i ω)|, we can see that |P i (α i ω)| is only the amplitude spectrum of the i-th segment sound pressure receiving signal after stretching or compressing in the time domain. Finally, the amplitude spectrum|P i (α i ω)| and |P M (ω)|, that is:

[0119]

[0120] Among them, w(α i ) represents the correlation coefficient; Cov represents the covariance; D represents the variance;

[0121]

[0122] in, Represents the correlation coefficient w(α i ) in the equation; arg represents the value of the independent variable when the expression reaches its maximum or minimum value; Represents traversal α i Make the expression value maximum;

[0123] In the above formula, the correlation coefficient w(α i ) corresponds to the scale factor of the maximum value It is the estimated scale factor of the i-th sound pressure signal relative to the M-th sound pressure signal. Since the vector hydrophone picks up the sound pressure and velocity signals synchronously at the same point, and the plane wave sound pressure and velocity waveforms are the same and only differ in amplitude, the scale factor It is also the scale factor of the i-th segment velocity signal relative to the M-th segment velocity signal, which can be used to perform Doppler compensation on both the sound pressure and velocity signals, and obtain the results of each segment after compensation based on the M-th segment:

[0124]

[0125] in, Represents the compensated sound pressure channel signal; Represents the compensated vibration velocity x-direction channel signal; Represents the compensated vibration velocity y-direction channel signal.

[0126] (2) Long-term coherent accumulation detection

[0127] For the sound pressure and velocity signals of each segment of the vector hydrophone after Doppler compensation, the next step is to solve the complex sound intensity.

[0128] First, the compensated signals are Fourier transformed to obtain the corresponding spectrum P i (ω), VX i (ω), VY i (ω), and then perform cross-spectral calculation on each segment to obtain the sound intensity I of each segment after motion compensation i (ω):

[0129]

[0130] Among them, IX i (ω) represents the sound intensity in the x direction after Doppler compensation; IY i (ω) represents the sound intensity in the y direction after Doppler compensation; I i (ω) represents the total sound intensity after Doppler compensation; Re represents the real part operation; the symbol “·” represents the dot multiplication operation; the superscript * represents the conjugate operation;

[0131] The sound intensity sequences after Doppler compensation in each segment are coherently accumulated to obtain the sound intensity detection result of the Mth segment, that is, the latest updated time period:

[0132]

[0133] Among them, I CPS (ω) represents the sound intensity detection result; M represents the number of segments;

[0134] After Doppler compensation, coherent accumulation is performed to obtain I CPS(ω), when the target moves at high speed, effective signal-to-noise ratio gain can still be obtained by increasing the processing time.

[0135] Example, first of all, a simulation application scenario of a specific implementation scheme is given. A moving target is set in the simulation to move in a uniform straight line at a speed of 20m / s. The closest distance between the target and the hydrophone is 500m. The movement trajectory is as follows: Figure 2 As shown in the figure, the radiated noise of the target is in the form of broadband noise plus line spectrum, with a signal bandwidth of 500-1400 Hz, including 13 line spectra with frequencies of [550, 585, 633, 684, 715, 752, 789, 822, 945, 985, 1023, 1145, 1285] Hz, and a line spectrum level signal-to-noise ratio of 13 dB. The target sound source level is 118 dB, and the ocean environment noise spectrum level is 60 dB.

[0136] In order to demonstrate the coherent accumulation of moving targets, the necessity of Doppler compensation processing is required.

[0137] In the first step, the detection results of the 20s signal under the assumption that the target is stationary are given, such as Figure 3 As shown. Figure 3 (a) is the time domain waveform of the received signal of the sound pressure channel, Figure 3 (b) is the result of cross-spectrum sound intensity detection using the three-channel signal of the vector hydrophone. When the target is stationary, the vector cross-spectrum sound intensity detection can give a better line spectrum detection result, the line spectrum output signal-to-noise ratio is very high, and the line spectrum frequency is consistent with the actual target radiation noise line spectrum frequency.

[0138] As a comparison, the results of vector cross-spectrum sound intensity detection without Doppler compensation when the target is moving are given, as shown in Figure 4 As shown. In addition, according to theoretical calculations, affected by the Doppler effect, the lowest frequency 550Hz and the highest frequency 1285Hz line spectrum signals emitted by the target at the position where it moves 20s away from the target become 546.064Hz and 1275.805Hz after the frequency shift at the vector hydrophone. Figure 4 (a) is the result of directly detecting the cross-spectral sound intensity using the first 20 seconds of the signal received by the vector hydrophone. Figure 4 As shown in the figure, when there is relative motion between the target and the hydrophone, if a longer integration time is used for detection at the current moment, the frequency resolution is very high, and the detection algorithm is very sensitive to the signal frequency change, which will cause a large drift in the signal line spectrum frequency and poor spectral peak aggregation, ultimately greatly reducing the output signal-to-noise ratio of the target line spectrum signal, and the effective target line spectrum cannot be extracted under a certain line spectrum detection threshold.

[0139] In order to reduce the sensitivity of spectrum estimation results to frequency drift, the conventional method is to use the segmented coherent accumulation method, divide the signal into 20 segments of 1 s each, and then perform coherent accumulation processing. The detection results of segmented processing are as follows: Figure 4 As shown in (b), it can be seen from the figure that the segmented detection processing can reduce the background noise fluctuation to a certain extent and improve the line spectrum output gain. However, due to the influence of the target motion, the line spectrum aggregation is still poor, which is not conducive to line spectrum detection. In addition, compared with the theoretical calculation, the line spectrum signal frequency actually received by the hydrophone at the current moment is still quite different. Figure 4 It can be seen from the results that there is a cross-correlation loss using the above two spectrum analysis methods, the obtained signal spectrum peaks are significantly broadened, and the line spectrum intensity is significantly reduced compared to when the target is stationary. The signal processing gain obtained by increasing the data samples is severely limited.

[0140] Therefore, the moving target Doppler compensation coherent detection method based on single vector hydrophone proposed in the present invention is very necessary.

[0141] In order to realize Doppler compensation of the cross-spectrum sound intensity detection of the vector hydrophone receiving signal, the present invention is based on Figure 1 The algorithm flow shown performs segmented Doppler compensation processing on the received data of each channel.

[0142] Specifically, the simulation parameters are set as follows: the length of the single snapshot data is 20 s, the length of each segment of the segmented data is 1 s, and the search range of the scale factor is [0.987, 1.013].

[0143] First, the scale factors of each segment data and the peak value of the relevant peak are traversed for the first snapshot of 20s received data. The process and results are as follows: Figure 5 As shown, from Figure 5 (a) In the process of searching through each segment of data, it can be seen that the correlation peak of each segment signal is more obvious than the current latest 1s received signal, and the scale factor is clearer. The search results of the scale factor are plotted in time series, such as Figure 5 As shown in (b), it can be seen from the figure that the scale factor shows a regular linear change over time, which is consistent with the state of the target doing linear motion.

[0144] Afterwards, the scale factors obtained by searching each segment are used to perform Doppler compensation on the three-channel data received by the vector hydrophone. After compensation, the cross-spectral sound intensity is solved, and then the sound intensity sequence after compensation of each segment is coherently accumulated to obtain the final cross-spectral sound intensity signal detection output result after Doppler compensation, as shown in Figure 1. Figure 6 As shown. Figure 6It can be seen that in the cross-spectrum sound intensity detection results after segmented Doppler compensation, the target line spectrum frequency is clear, the aggregation is strong, the processing gain is significantly improved, and the line spectrum frequency value detected after compensation is highly consistent with the line spectrum frequency value after the Doppler frequency shift at the hydrophone receiving end at 20s obtained by theoretical calculation. This result effectively verifies that the Doppler compensation coherent accumulation method based on single vector hydrophone proposed in the present invention can greatly improve the line spectrum detection performance of moving targets.

[0145] The lake test data were used for further verification and analysis.

[0146] The test situation on the lake is that a yacht target is circling at a high speed of 16 knots, and a single vector hydrophone is hung on the side of the experimental station. The distance between the yacht and the vector hydrophone is within the range of 50m to 250m. The GPS positioning trajectory of the yacht target is as follows Figure 7 The processing parameters are set as follows: the length of the single snapshot data is 20s, the length of each segment of the segment data is 1s, and the processing bandwidth is 100Hz to 5kHz.

[0147] Consistent with the implementation steps of the above simulation verification, the scale factor of the single snapshot data is first traversed and searched. The process and results are as follows: Figure 8 As shown in the figure, the segmented scale factor search for the lake test data still has a good effect, the correlation peak is clear, and the scale factor corresponding to each segment can be effectively extracted for Doppler compensation.

[0148] After that, the sound pressure and velocity signals actually received by the vector hydrophone are segmented for Doppler compensation, and the cross-spectrum sound intensity is solved, and finally coherent accumulation is performed to obtain the compensated cross-spectrum sound intensity detection result, as shown in Fig. 9 and Fig.10 In addition, Fig. 9 and Fig.10 The results without Doppler compensation are also given for comparison. Fig. 9 The detection results of the full processing frequency band and Fig.10 From the detailed display results of the local magnification of the frequency axis, it can be concluded that in the detection results after Doppler compensation, the peak of the target radiation noise line spectrum is sharper, the concentration is better, and the line spectrum output signal-to-noise ratio is improved by about 2dB.

[0149] It can also be seen that the line spectrum frequency position after Doppler compensation is significantly different from that before compensation. According to theoretical and simulation analysis, the line spectrum peak position obtained after Doppler compensation is more real and effective, which is conducive to the subsequent line spectrum tracking and azimuth estimation of the target.

[0150] The present invention also provides a moving target Doppler compensation coherent detection system based on a single vector hydrophone. The moving target Doppler compensation coherent detection system based on a single vector hydrophone can be realized by executing the process steps of the moving target Doppler compensation coherent detection method based on a single vector hydrophone, that is, those skilled in the art can understand the moving target Doppler compensation coherent detection method based on a single vector hydrophone as a preferred implementation of the moving target Doppler compensation coherent detection system based on a single vector hydrophone.

[0151] According to the present invention, a moving target Doppler compensation coherent detection system based on a single vector hydrophone includes: a module M1: collecting a received signal of the single vector hydrophone, segmenting it, and obtaining segmented data;

[0152] Module M2: estimating the scale factor of the received data of the current segment according to the segmented data;

[0153] Module M3: compensating the corresponding segmented data according to the scale factor to obtain a compensated signal;

[0154] Module M4: coherently accumulates and processes the compensated signal to obtain a sound intensity detection result, that is, a signal-to-noise ratio gain.

[0155] The scale factor is the Doppler coefficient.

[0156] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the moving target Doppler compensation coherent detection method based on a single vector hydrophone are implemented.

[0157] An electronic device provided according to the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the moving target Doppler compensation coherent detection method based on a single vector hydrophone are implemented.

[0158] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0159] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A moving target Doppler compensation coherent detection method based on a single vector hydrophone, characterized in that: include: Step S1: collecting the received signal of the single vector hydrophone, segmenting it, and obtaining segmented data; Step S2: estimating the scale factor of the received data of the current segment according to the segmented data; Step S3: compensating the corresponding segmented data according to the scale factor to obtain a compensated signal; Step S4: coherently add and process the compensated signal to obtain a sound intensity detection result, namely, a signal-to-noise ratio gain. The scale factor is the Doppler coefficient.

2. The moving target Doppler compensation coherent detection method based on single vector hydrophone according to claim 1 is characterized in that: In the step S1, it includes: Step S1.1: collecting the received signal of a single vector hydrophone; Step S1.2: Divide the received signal into M segments to obtain segmented data; In the step S2, it includes: Step S2.1: Setting the search range of the scale factor; Step S2.2: According to the search range, traverse the scale factor, resample the segmented data of the first (M-1) segments, estimate the received signal corresponding to the scale factor, and obtain an evaluation result; In step S2.1, the search range of the scale factor is expressed mathematically as follows: Among them, α max Indicates the maximum value of the scale factor; α min Indicates the minimum value of the scale factor; v max is the maximum speed of the target to be detected, c is the underwater sound speed; In step S2.2, the evaluation result is expressed mathematically as follows: p i (t / α i ), i = 1, 2, ..., (M-1) (3) where p i (t / α i ) represents a received signal as an evaluation result; The evaluation result and the sound pressure signal are respectively subjected to Fourier transform to obtain the evaluation result modulus value, i.e. |α i P ii (αω)| and the modulus of the sound pressure signal, that is, |P M (ω)|.

3. The moving target Doppler compensation coherent detection method based on single vector hydrophone according to claim 2 is characterized in that: In the step S3, a correlation coefficient is calculated according to the evaluation result of the scale factor, and the sound pressure and vibration velocity signals of the received signal are compensated based on the correlation coefficient to obtain a compensated result; The mathematical expression of the correlation coefficient is: Among them, w(α i ) represents the correlation coefficient; Cov represents the covariance; D represents the variance; where |P i (α i ω)| is the amplitude spectrum of the i-th segment sound pressure receiving signal after stretching or compression in the time domain, obtained based on the evaluation result modulus; The scale factor corresponding to the maximum value of the correlation coefficient is expressed as follows: Among them, arg represents the value of the independent variable when the expression reaches the maximum or minimum value; Represents traversal α i Make the expression value maximum; The mathematical expression of the result after compensation is: in, Represents the compensated sound pressure channel signal; Represents the compensated vibration velocity x-direction channel signal; Represents the compensated vibration velocity y-direction channel signal.

4. The moving target Doppler compensation coherent detection method based on single vector hydrophone according to claim 3 is characterized in that: In the step S4, it includes: Step S4.1: Fourier transform the compensated result to obtain a corresponding spectrum; Step S4.2: according to the frequency spectrum, obtaining the sound intensity of each segment after motion compensation; Step S4.3: coherently accumulate and process the sound intensity sequences after compensation in each segment to obtain the sound intensity detection results; In step S4.2, the spectrum includes P i (ω), VX i (ω) and VY i (ω), the corresponding sound intensity, mathematical expression is: Among them, IX i (ω) represents the sound intensity in the x direction after Doppler compensation; IY i (ω) represents the sound intensity in the y direction after Doppler compensation; I i (ω) represents the total sound intensity after Doppler compensation; Re represents the real part operation; the symbol "·" represents the dot multiplication operation; the superscript * represents the conjugate operation; In step S4.3, the sound intensity detection result is expressed mathematically as follows: Among them, I CPS (ω) represents the sound intensity detection result; M represents the number of segments.

5. A moving target Doppler compensation coherent detection system based on a single vector hydrophone, characterized in that: It includes: module M1: collecting the receiving signal of the single vector hydrophone, segmenting it, and obtaining segmented data; Module M2: estimating the scale factor of the received data of the current segment according to the segmented data; Module M3: compensating the corresponding segmented data according to the scale factor to obtain a compensated signal; Module M4: coherently accumulates and processes the compensated signal to obtain a sound intensity detection result, that is, a signal-to-noise ratio gain. The scale factor is the Doppler coefficient.

6. The moving target Doppler compensation coherent detection method based on single vector hydrophone according to claim 5, characterized in that: The module M1 includes: Module M1.1: Collect the received signal of a single vector hydrophone; Module M1.2: Divide the received signal into M segments to obtain segmented data; The module M2 includes: Module M2.1: Set the search range of the scale factor; Module M2.2: according to the search range, traverse the scale factor, resample the segmented data of the first (M-1) segments, estimate the received signal corresponding to the scale factor, and obtain an evaluation result; In the module M2.1, the search range of the scale factor is expressed as follows: Among them, α max Indicates the maximum value of the scale factor; α min Indicates the minimum value of the scale factor; v max is the maximum speed of the target to be detected, c is the underwater sound speed; In the module M2.2, the evaluation result is expressed mathematically as follows: p i (t / α i ), i = 1, 2, ..., (M-1) (3) where p i (t / α i ) represents a received signal as an evaluation result; The evaluation result and the sound pressure signal are respectively subjected to Fourier transform to obtain the evaluation result modulus value, i.e. |α i P i (αω)| and the modulus of the sound pressure signal, that is, |P M (ω)|.

7. The moving target Doppler compensation coherent detection system based on single vector hydrophone according to claim 6, characterized in that: In the module M3, a correlation coefficient is calculated according to the evaluation result of the scale factor, and the sound pressure and vibration velocity signals of the received signal are compensated based on the correlation coefficient to obtain a compensated result; The mathematical expression of the correlation coefficient is: Among them, w(α i ) represents the correlation coefficient; Cov represents the covariance; D represents the variance; where |P i (α i ω)| is the amplitude spectrum of the i-th segment sound pressure receiving signal after stretching or compression in the time domain, obtained based on the evaluation result modulus; The scale factor corresponding to the maximum value of the correlation coefficient is expressed as follows: Among them, arg represents the value of the independent variable when the expression reaches the maximum or minimum value; Represents traversal α i Make the expression value maximum; The mathematical expression of the result after compensation is: in, Represents the compensated sound pressure channel signal; Represents the compensated vibration velocity x-direction channel signal; Represents the compensated vibration velocity y-direction channel signal.

8. The moving target Doppler compensation coherent detection system based on single vector hydrophone according to claim 7, characterized in that: The module M4 includes: Module M4.1: Fourier transform the compensated result to obtain the corresponding spectrum; Module M4.2: according to the frequency spectrum, obtaining the sound intensity of each segment after motion compensation; Module M4.3: Coherently accumulate and process the sound intensity sequence after compensation in each segment to obtain the sound intensity detection result; In the module M4.2, the spectrum includes P i (ω), VX i (ω) and VYi i (ω), the corresponding sound intensity, mathematical expression is: Among them, IX i (ω) represents the sound intensity in the x direction after Doppler compensation; IY i (ω) represents the sound intensity in the y direction after Doppler compensation; I i (ω) represents the total sound intensity after Doppler compensation; Re represents the real part operation; the symbol "·" represents the dot multiplication operation; the superscript * represents the conjugate operation; In the module M4.3, the sound intensity detection result is expressed as follows: Among them, I CPS (ω) represents the sound intensity detection result; M represents the number of segments.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the moving target Doppler compensation coherent detection method based on a single vector hydrophone according to any one of claims 1 to 4 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of the moving target Doppler compensation coherent detection method based on a single vector hydrophone according to any one of claims 1 to 4 are implemented.

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