Moving target line spectrum detection method based on trajectory integration
By using a trajectory integral-based method to scan target motion parameters for phase compensation, the problem of poor detection performance when the target line spectrum signal is weak in the existing technology is solved, and high time integration gain and target parameter estimation are achieved.
Patent Information
- Application Number
- CN202511620003.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-06
- Publication Date
- 2025-12-19
AI Technical Summary
Existing methods suffer from reduced time integration gain when the target line spectrum signal is weak, resulting in poor detection performance of moving target line spectrum. Furthermore, the Doppler effect caused by motion introduces errors in higher-order phase components.
By employing a trajectory integration-based method, Fourier transform and trajectory integration are performed by dividing the signal integration time window to scan the target's motion parameters, achieving phase compensation, avoiding errors in higher-order phase components, and improving detection performance.
High time integral gain processing was achieved, which improved the performance of moving target line spectrum detection, obtained target parameter estimation results, and solved the problem of difficult target parameter estimation under a single platform.
Smart Images
Figure CN121165026A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of underwater acoustic passive detection technology, specifically relating to a method for detecting the line spectrum of moving targets based on trajectory integration. Background Technology
[0002] Most surface ships emit radiation signals containing both line spectrum and continuous spectrum signals. Compared to continuous spectrum signals, line spectrum signals are more stable and have higher intensity, making them crucial for passive detection and identification. Line spectrum detection methods are commonly used to detect and locate such ships; however, small-scale receiver arrays on single platforms struggle to achieve effective spatial processing gain, requiring long integration times to obtain high temporal processing gain. Furthermore, if the target moves, the Doppler effect will distort the target line spectrum. Traditional FFT methods cannot achieve long-term integration gain due to signal waveform distortion, only obtaining coherent integration gain within a finite integration time with a small Doppler effect. Current methods improve the line spectrum gain of moving targets by approximating the phase change of the moving target line spectrum signal as a finite order, thereby enhancing line spectrum detection capabilities. Reference 1 (Lan H, Paul R.White, Li N, et al. Coherently averaged powerspectral estimate for signal detection. Signal Process., 2019; 169: Art. no.107414) utilizes FFT to directly compensate for the first-order phase. Reference 2 (Zhang L, Piao S, Guo J, et al. Passivetone detection for moving targets based on long time coherent integration. IEEE Journal of oceanic engineering., 2023; 48(3): 820−836) proposes a phase compensation factor search algorithm based on Laden polynomial Fourier transform, which obtains higher coherent integration gain by utilizing the second-order phase of the moving target line spectrum signal.
[0003] In summary, current line spectrum detection methods primarily utilize the first or second-order phase of the line spectrum. Time integration gain can be obtained through coherent integration within a finite integration time, thereby improving line spectrum detection performance. However, when the target line spectrum signal is weak, a longer integration time is required, and the Doppler effect caused by motion becomes greater. Due to the existence of higher-order phase components, current phase approximation methods introduce errors in higher-order phase components, and severe phase mismatch leads to a decrease in integration gain, affecting the detection performance of moving target line spectra. Summary of the Invention
[0004] The purpose of this invention is to address the problem that the time integral gain of the line spectrum in existing methods decreases when the target line spectrum signal is weak, resulting in poor performance in moving target line spectrum detection. Therefore, this invention proposes a moving target line spectrum detection method based on trajectory integral.
[0005] The technical solution adopted by the present invention to solve the above-mentioned technical problems is: a method for detecting the line spectrum of a moving target based on trajectory integral, the method specifically including the following steps:
[0006] Step 1: Acquire the signal using an integration time window of length T seconds, and then divide the signal within the integration time window into T segments;
[0007] Step 2: Perform Fourier transform on each segment of the signal obtained from the time domain, that is, transform each segment of the signal from the time domain to the frequency domain.
[0008] Step 3: Obtain the trajectory integration results of the target line spectrum under different scanning parameters based on the signal converted to the frequency domain;
[0009] Step 4: Determine the target's motion parameters and line spectrum frequency based on the trajectory integration results from Step 3. Obtain the moving target line spectrum detection results within the current integration time window based on the target's motion parameters and line spectrum frequency.
[0010] Step 5: Obtain new signals to be processed by continuing to slide the integration time window. After dividing the new signals to be processed into T segments, return to step 2.
[0011] Furthermore, in step one, the length of each segment of the signal is 1 second.
[0012] Furthermore, the specific process of step three is as follows:
[0013] Step 31: Within the current integration time window, record the initial horizontal position of the target relative to the receiving hydrophone as... The nearest passing distance of the target relative to the receiving hydrophone is denoted as The target's speed is denoted as ;
[0014] Will The initial search value is denoted as ,Will The initial search value is denoted as ,Will The initial search value is denoted as and set them respectively , and The search step size;
[0015] The resulting search values are denoted as follows:
[0016]
[0017] in, Let be the search step size of the target relative to the initial horizontal position of the receiving hydrophone. Let be the search step size relative to the nearest passing distance of the target to the receiving hydrophone. The search step size is the target velocity. , The total number of search values for the target motion speed. , The total number of search values for the target relative to the nearest passing distance of the receiving hydrophone. , The total number of search values for the target relative to the initial horizontal position of the receiving hydrophone. The first [value] represents the target's initial horizontal position relative to the receiving hydrophone. One search value, The first term represents the closest passing distance of the target relative to the receiving hydrophone. One search value, The first digit representing the target's velocity One search value;
[0018] Step 32: For each set of search values, scan at different frequencies to obtain the trajectory integral result corresponding to each scan.
[0019] Furthermore, in step four, the motion parameters of the target and the line spectrum frequency of the target are determined based on the trajectory integration result of step three. The specific process is as follows:
[0020] For any trajectory integral result corresponding to a scan, determine whether there is a coherent peak in the trajectory integral result of the current scan that is greater than the line spectrum threshold.
[0021] If the trajectory integral result of the current scan contains a coherent peak greater than the line spectrum threshold, then the search value corresponding to the trajectory integral result of the current scan is the target's motion parameter. , and The scanning frequency corresponding to the trajectory integral result of the current scan is the target's line spectrum frequency. ;
[0022] If there is no coherent peak greater than the line spectrum threshold in the trajectory integral result of the current scan, then the trajectory integral result of the current scan does not correspond to the target.
[0023] The above method is used to judge the trajectory integration results corresponding to each scan.
[0024] Furthermore, the trajectory integration result in step three-two is as follows:
[0025]
[0026] in, Indicates the first The Fourier transform result corresponding to the segment signal, Represents the imaginary unit. Indicates frequency, This indicates the depth difference between the target and the receiving hydrophone. It indicates the speed of sound.
[0027] Furthermore, the receiving hydrophone is a submersible buoy.
[0028] Furthermore, the receiving hydrophone is WG.
[0029] Furthermore, the target moves at a constant velocity in a straight line.
[0030] Furthermore, in step four, the moving target line spectrum detection result within the current integration time window is obtained based on the target's motion parameters and the target's line spectrum frequency. The specific process is as follows:
[0031]
[0032] in, This indicates the line spectrum detection result of the target.
[0033] The beneficial effects of this invention are:
[0034] This invention performs phase compensation on the received signal at different times by scanning three parameters: the target's motion speed, the closest passing distance, and the initial horizontal position relative to the receiving hydrophone. Moreover, it does not require a phase approximation process, thus avoiding high-order component errors caused by phase approximation. Based on the trajectory integration results obtained by scanning at different motion parameters and frequencies, this invention achieves high time integration gain processing of the target line spectrum, improves the detection performance of moving target line spectrum, and obtains the target parameter estimation results, solving the problem of difficult target parameter estimation under a single platform. Attached Figure Description
[0035] Figure 1 This is a flowchart of a moving target line spectrum detection method based on trajectory integral according to the present invention;
[0036] Figure 2 It is a system model of target motion;
[0037] Figure 3 It is the phase compensation result of the target line spectrum under different parameters;
[0038] Figure 4 It is the integral frequency history of a single target line spectrum trajectory;
[0039] Figure 5 This is a comparison of the outputs of CAPSE, second-order coefficient scan, and trajectory integration methods in the case of a single target.
[0040] Figure 6 This is a comparison of the processing gain of CAPSE, second-order coefficient scan, and trajectory integration methods as a function of integration time.
[0041] Figure 7 This is a comparison of the detection probabilities of CAPSE, second-order coefficient scanning, and trajectory integration methods under different input signal-to-noise ratios.
[0042] Figure 8 This is a comparison of the outputs of CAPSE, second-order coefficient scan, and trajectory integration methods in the case of two targets. Detailed Implementation
[0043] Specific implementation method one: Combining Figure 1 This embodiment describes a method for detecting the line spectrum of a moving target based on trajectory integral. The method specifically includes the following steps:
[0044] Step 1: Acquire the signal using an integration time window of length T seconds, and then divide the signal within the integration time window into T segments;
[0045] Step 2: Perform Fourier transform on each segment of the signal obtained from the time domain, that is, transform each segment of the signal from the time domain to the frequency domain.
[0046] Step 3: Obtain the trajectory integration results of the target line spectrum under different scanning parameters based on the signal converted to the frequency domain;
[0047] Step 4: Determine the target's motion parameters and line spectrum frequency based on the trajectory integration results from Step 3. Obtain the moving target line spectrum detection results within the current integration time window based on the target's motion parameters and line spectrum frequency.
[0048] Step 5: Obtain new signals to be processed by continuing to slide the integration time window. After dividing the new signals to be processed into T segments, return to step 2.
[0049] By continuously sliding the integration time window, the detection results of the moving target line spectrum under each integration time window can be obtained, that is, the change history diagram of the line spectrum frequency and the change of the target motion parameters can be obtained.
[0050] Specific Implementation Method Two: This implementation method is a further limitation of Specific Implementation Method One. In step one, the length of each segment of signal obtained is 1 second.
[0051] The other steps and parameters are the same as in Specific Implementation Method 1.
[0052] Specific Implementation Method Three: This implementation method is a further limitation of Specific Implementation Method Two. The specific process of step three is as follows:
[0053] Step 31: Within the current integration time window, record the initial horizontal position of the target relative to the receiving hydrophone as... This represents the horizontal position of the target relative to the receiving hydrophone at the beginning of the current integration time window. The closest passing distance of the target relative to the receiving hydrophone is denoted as... The target's speed is denoted as ;
[0054] It should be noted that the initial horizontal position of the target relative to the receiving hydrophone is a relative value at the start of the current integration time window;
[0055] Will The initial search value is denoted as ,Will The initial search value is denoted as ,Will The initial search value is denoted as and set them respectively , and The search step size;
[0056] The resulting search values are denoted as follows:
[0057]
[0058] in, Let be the search step size of the target relative to the initial horizontal position of the receiving hydrophone. Let be the search step size relative to the nearest passing distance of the target to the receiving hydrophone. The search step size is the target velocity. , The total number of search values for the target motion speed. , The total number of search values for the target relative to the nearest passing distance of the receiving hydrophone. , The total number of search values for the target relative to the initial horizontal position of the receiving hydrophone. The first [value] represents the target's initial horizontal position relative to the receiving hydrophone. One search value, The first term represents the closest passing distance of the target relative to the receiving hydrophone. One search value, The first digit representing the target's velocity One search value;
[0059] Step 32: For each set of search values, scan at different frequencies to obtain the trajectory integral result corresponding to each scan.
[0060] The other steps and parameters are the same as in Specific Implementation Method Two.
[0061] Specific Implementation Method Four: This implementation method further defines Specific Implementation Method Three. In step four, the motion parameters of the target and the line spectrum frequency of the target are determined based on the trajectory integration result of step three. The specific process is as follows:
[0062] For any trajectory integral result corresponding to a scan, determine whether there is a coherent peak in the trajectory integral result of the current scan that is greater than the line spectrum threshold.
[0063] If the trajectory integral result of the current scan contains a coherent peak greater than the line spectrum threshold, then the search value corresponding to the trajectory integral result of the current scan is the target's motion parameter. , and The scanning frequency corresponding to the trajectory integral result of the current scan is the target's line spectrum frequency. ;
[0064] If there is no coherent peak greater than the line spectrum threshold in the trajectory integral result of the current scan, then the trajectory integral result of the current scan does not correspond to the target.
[0065] The above method is used to judge the trajectory integration results corresponding to each scan.
[0066] The other steps and parameters are the same as in Specific Implementation Method 3.
[0067] The position of the receiving hydrophone is fixed at the coordinates. The location, i.e., the position of the receiving hydrophone, is known. The initial horizontal position of the target relative to the receiving hydrophone. The nearest passing distance of the target relative to the receiving hydrophone. For the target speed, The distance between the target and the receiving hydrophone;
[0068]
[0069] Based on the change in distance between the target and the receiving hydrophone, and using the known speed of sound c, the corresponding transmit and receive time difference can be calculated. Thus, the target line spectrum is obtained. Phase compensation amount ;
[0070]
[0071] For the three parameters—target velocity, closest passing distance, and initial horizontal position—different combinations of search parameter values correspond to different motion trajectories within the integration time; that is, different combinations of search parameter values correspond to different phase compensation amounts. By setting the search range and search step size for the three parameters, we can obtain... The system searches for parameter values in groups, each with a corresponding phase compensation value. When the phase compensation value of a group of parameter values matches the phase compensation value corresponding to the target's trajectory, i.e., when this group of parameter values matches the target's trajectory parameters, a coherent peak appears in the trajectory integral result. The parameter corresponding to the coherent peak is then the target's trajectory parameter. When multiple targets exist, multiple coherent peaks can be detected.
[0072] Specific Implementation Method Five: This implementation method differs from Specific Implementation Method Four in that the trajectory integration result in step three, step two is as follows:
[0073]
[0074] in, Indicates the first The Fourier transform result corresponding to the segment signal, Represents the imaginary unit. Indicates frequency, This represents the depth difference between the target and the receiving hydrophone (this invention assumes the target is moving in the horizontal plane, therefore the depth difference is...). (Unchanged) It indicates the speed of sound.
[0075] The other steps and parameters are the same as in Specific Implementation Method Four.
[0076] Specific Implementation Method Six: This implementation method is a further limitation of Specific Implementation Method Five, wherein the receiving hydrophone is a submersible buoy.
[0077] The other steps and parameters are the same as in Specific Implementation Method 5.
[0078] Specific Implementation Method Seven: This implementation method is a further limitation of Specific Implementation Method Five, wherein the receiving hydrophone is WG (Wave Glider).
[0079] The other steps and parameters are the same as in Specific Implementation Method 5.
[0080] The platforms that can be used in this invention include, but are not limited to, the platforms described above, and may also be other smaller platforms.
[0081] Specific Implementation Method Eight: This implementation method is a further limitation of Specific Implementation Method Six or Seven, wherein the target moves in uniform linear motion.
[0082] The other steps and parameters are the same as in specific implementation methods six or seven.
[0083] It should be noted that the method of this invention is applicable even if the target does not move at a strictly uniform linear speed; the target only needs to move at an approximately uniform linear speed.
[0084] Specific Implementation Method Nine: This implementation method further defines Specific Implementation Method Eight. In step four, the moving target line spectrum detection result within the current integration time window is obtained based on the target's motion parameters and the target's line spectrum frequency. The specific process is as follows:
[0085]
[0086] in, This indicates the line spectrum detection result of the target.
[0087] The other steps and parameters are the same as in Specific Implementation Method 8.
[0088] Similarly, when multiple targets are identified through trajectory integration, the method of this embodiment can be used to determine the line spectrum detection results of multiple targets.
[0089] Experimental Section
[0090] 1. Consider a single-frequency line spectrum target moving in a straight line. The target's motion is as follows: Figure 2 As shown, the target signal frequency is 250 Hz, the input signal-to-noise ratio is 0 dB, the receiving hydrophone depth is 2600 m, the speed is 3 m / s, the closest passing distance is 1500 m, and the initial horizontal position of the target is -2000 m. Long-time integration processing is performed according to the steps of this invention:
[0091] First, the integration time is set to 1000 s, and the received signal is divided into 1-s segments within the integration time. Then, a Fourier transform is used to convert the signal within each 1-s segment from the time domain to the frequency domain. Next, the scanning range and scanning step size of the parameters are set. For the three parameters—target velocity, nearest passing distance, and initial horizontal position—different parameters correspond to different trajectories within the integration time, i.e., different phase compensation amounts. By setting the search range and search step size for the three parameters, several sets of search parameter values can be obtained, each with a corresponding phase compensation amount. Specifically, the velocity scanning range is 1~5 m / s, and the velocity scanning step size is 1 m / s; the initial horizontal position scanning range is -4000~4000 m, and the initial horizontal position scanning step size is 10 m; the nearest passing distance scanning range is 1000~2000 m, and the nearest passing distance scanning step size is 10 m. The trajectory integration results of the target line spectrum under different parameters are as follows: Figure 3 As shown. When the phase compensation amount matches the phase compensation amount corresponding to the target's motion trajectory, a unique coherent peak can be obtained. The corresponding parameters are the target's motion parameters, with a velocity of 3 m / s, a closest passing distance of 1500 m, and an initial horizontal position of -2000 m. Figure 4 As shown, the corresponding trajectory integral spectrum history can be obtained by sliding the time window. Selecting one time slice, the output results of CAPSE, second-order coefficient scan, and the trajectory integral method of this invention are compared, as shown below. Figure 5 As shown, the output amplitude of the trajectory integral is higher than that of CAPSE and second-order coefficient scan, which can better improve the line spectrum detection performance. Figure 6 As shown, the processing gain of the three methods varies with the integration time by changing the integration time. The theoretical gains of the three methods are shown in Table 1.
[0092] Table 1
[0093]
[0094] Depend on Figure 6 It is evident that the processing gain of trajectory integration is closer to the theoretical gain. However, CAPSE and second-order coefficient scan introduce higher-order component errors due to increased integration time, resulting in output gains lower than the theoretical gain. With a false alarm probability set to 0.001, Figure 7 By varying the signal-to-noise ratio (SNR), 1000 Monte Carlo simulations were performed, and the simulation results were averaged. The detection probability results of CAPSE, second-order coefficient scanning, and trajectory integration methods under different input SNRs were compared. It is evident that the trajectory integration method of this invention can achieve line spectrum detection performance superior to CAPSE and second-order coefficient scanning methods.
[0095] 2. There are two line spectrum targets. The depth of the receiving hydrophone is 2600 m. Target 1 has a frequency of 250 Hz, an input signal-to-noise ratio of 0 dB, a speed of 3 m / s, a closest passing distance of 1500 m, and an initial horizontal position of -2000 m. Target 2 has a frequency of 150 Hz, an input signal-to-noise ratio of 0 dB, a speed of 5 m / s, a closest passing distance of 1800 m, and an initial horizontal position of -3000 m. Figure 8 For the trajectory integration processing of dual-target line spectrum, the output spectrum of CAPSE and second-order phase coefficient scanning is compared, and it can be seen that the trajectory integration method of the present invention solves the high-order component error caused by phase approximation.
[0096] The above examples of the present invention are merely illustrative of the computational model and process of the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is impossible to exhaustively list all possible implementations here. Any obvious variations or modifications derived from the technical solutions of the present invention are still within the scope of protection of the present invention.
Claims
1. A method for detecting the line spectrum of a moving target based on trajectory integral, characterized in that, The method specifically includes the following steps: Step 1: Acquire the signal using an integration time window of length T seconds, and then divide the signal within the integration time window into T segments; Step 2: Perform Fourier transform on each segment of the signal obtained from the time domain, that is, transform each segment of the signal from the time domain to the frequency domain. Step 3: Obtain the trajectory integration results of the target line spectrum under different scanning parameters based on the signal converted to the frequency domain; Step 4: Determine the target's motion parameters and line spectrum frequency based on the trajectory integration results from Step 3. Obtain the moving target line spectrum detection results within the current integration time window based on the target's motion parameters and line spectrum frequency. Step 5: Obtain new signals to be processed by continuing to slide the integration time window. After dividing the new signals to be processed into T segments, return to step 2.
2. The method for detecting the line spectrum of a moving target based on trajectory integral according to claim 1, characterized in that, In step one, the length of each segment of the signal is 1 second.
3. The method for detecting the line spectrum of a moving target based on trajectory integral according to claim 2, characterized in that, The specific process of step three is as follows: Step 31: Within the current integration time window, record the initial horizontal position of the target relative to the receiving hydrophone as... The nearest passing distance of the target relative to the receiving hydrophone is denoted as The target's speed is denoted as ; Will The initial search value is denoted as ,Will The initial search value is denoted as ,Will The initial search value is denoted as and set them respectively , and The search step size; The resulting search values are denoted as follows: in, Let be the search step size of the target relative to the initial horizontal position of the receiving hydrophone. Let be the search step size relative to the nearest passing distance of the target to the receiving hydrophone. The search step size is the target velocity. , The total number of search values for the target motion speed. , The total number of search values for the target relative to the nearest passing distance of the receiving hydrophone. , The total number of search values for the target relative to the initial horizontal position of the receiving hydrophone. The first [value] represents the target's initial horizontal position relative to the receiving hydrophone. One search value, The first term represents the closest passing distance of the target relative to the receiving hydrophone. One search value, The first digit representing the target's velocity One search value; Step 32: For each set of search values, scan at different frequencies to obtain the trajectory integral result corresponding to each scan.
4. The method for detecting the line spectrum of a moving target based on trajectory integral according to claim 3, characterized in that, In step four, the motion parameters and line spectrum frequencies of the target are determined based on the trajectory integration results from step three. The specific process is as follows: For any trajectory integral result corresponding to a scan, determine whether there is a coherent peak in the trajectory integral result of the current scan that is greater than the line spectrum threshold. If the trajectory integral result of the current scan contains a coherent peak greater than the line spectrum threshold, then the search value corresponding to the trajectory integral result of the current scan is the target's motion parameter. , and The scanning frequency corresponding to the trajectory integral result of the current scan is the target's line spectrum frequency. ; If there is no coherent peak greater than the line spectrum threshold in the trajectory integral result of the current scan, then the trajectory integral result of the current scan does not correspond to the target. The above method is used to judge the trajectory integration results corresponding to each scan.
5. The method for detecting the line spectrum of a moving target based on trajectory integral according to claim 4, characterized in that, The trajectory integration result in step three-two is as follows: in, Indicates the first The Fourier transform result corresponding to the segment signal, Represents the imaginary unit. Indicates frequency, This indicates the depth difference between the target and the receiving hydrophone. It indicates the speed of sound.
6. The method for detecting the line spectrum of a moving target based on trajectory integral according to claim 5, characterized in that, The receiving hydrophone is a submersible buoy.
7. The method for detecting the line spectrum of a moving target based on trajectory integral according to claim 5, characterized in that, The receiving hydrophone is WG.
8. A method for detecting the line spectrum of a moving target based on trajectory integral according to claim 6 or 7, characterized in that, The target is moving at a constant speed in a straight line.
9. The method for detecting the line spectrum of a moving target based on trajectory integral according to claim 8, characterized in that, In step four, the moving target line spectrum detection result within the current integration time window is obtained based on the target's motion parameters and the target's line spectrum frequency. The specific process is as follows: in, This indicates the line spectrum detection result of the target.