A method for estimating the range and trajectory of a passive sonar target

Abstract

This invention relates to the field of underwater acoustic detection technology, and provides a method for estimating the range and trajectory of moving targets using passive sonar. By exploring the specific geometric relationship between the sonar platform and the target platform, an analytical model for estimating the target's heading, speed, range, and trajectory using passive sonar on a moving platform is derived. Using observations of the target's azimuth and spectral frequency at three time intervals, the range, heading, speed, and trajectory of the passive target are estimated without iterative calculations. This method remains applicable even when the sonar platform is stationary, demonstrating strong versatility. Furthermore, a correction method is proposed to address the range estimation errors caused by platform motion and sound propagation delay. Through continuous observation and dynamic calculation, a target trajectory map similar to that of active sonar is obtained, providing richer and more important target indication information for passive target tracking, identification, and command decisions.

Description

Technical Field

[0001] This invention relates to the field of underwater acoustic detection technology, and in particular to a method for estimating the distance and trajectory of a passive sonar target. Background Technology

[0002] The azimuth, range, motion parameters, and trajectory of passive sonar targets are crucial target information elements. They are important bases for target situation estimation, threat estimation, and command decision-making, and are also important research topics in underwater acoustic signal and information processing.

[0003] Passive sonar is mainly deployed in two ways: one is on a stationary platform in a fixed location, such as a fixed underwater array; the other is on a mobile platform, such as a submarine or surface ship. Passive sonar installed on a mobile platform is the most prevalent form currently and in the future. Because passive sonar can only estimate the target's bearing and cannot provide the target's range, its practical efficiency is greatly limited. Therefore, target range estimation using passive sonar has become a major issue in the field of underwater acoustic signal processing.

[0004] Currently, the main methods for passive target range estimation include: First, the matching field method based on prior information about the marine environment, which requires relatively accurate information about the underwater acoustic environment and involves significant computational load; second, the three-subarray ranging method, whose accuracy depends on the subarray spacing and the target distance, and is generally suitable for situations where the target distance is relatively short; and third, the range estimation method based on shallow-sea waveguide invariants, which uses the interference fringes generated by the target motion in the LOFAR spectrum to estimate the target distance by obtaining the slope of the fringes, and this method is mainly suitable for shallow seas and situations where the target distance is relatively short. For passive sonar on moving platforms, the Target Motion Analysis (TMA) method is a classic method for solving the estimation of moving target range and motion parameters. It is a pure azimuth target motion parameter estimation method that uses the target azimuth time-series information observed during the movement of the passive sonar platform to establish measurement equations and target motion state equations. Based on techniques such as least squares, Kalman filtering, and insensitive filtering, the target position and motion parameters are estimated. This method requires that the sonar platform is moving and that the target state must be observable. However, when both the sonar platform and the target platform are moving at a constant velocity in a straight line, the target state established by the TMA method is unobservable. To improve observability, the sonar platform needs to perform at least one turning maneuver during the target motion parameter calculation process. In practical applications, this method mainly suffers from problems such as the need for the sonar platform to maneuver, long computation time (generally 10-30 minutes for underwater targets), and the algorithm's tendency to diverge or even fail to provide a solution, which seriously affects the effectiveness of practical applications.

[0005] Target localization based on Doppler frequency shift characteristics has wide applications in radar, radio communication, and radio reconnaissance. Existing methods all rely on the Doppler frequency shift over a certain observation period for localization or velocity estimation. Because radar observes targets (especially aerial targets) at high speeds, and radar and radio communication operate at very high frequencies, the Doppler frequency shift phenomenon is very pronounced, and the Doppler frequency shift over a certain observation period is relatively large. Therefore, its application in radar, communication, and reconnaissance fields has been quite successful. However, underwater targets (especially those moving quietly underwater) move at slow speeds, and passive sonar operates at low frequencies. In this context, the Doppler frequency shift of the signal over a certain period is very small. Therefore, target velocity estimation or localization methods based on conventional Doppler frequency shift characteristics are unstable, have long convergence times (or even fail to converge), and cannot meet the requirements for underwater acoustic target localization.

[0006] Currently, for stationary underwater acoustic systems, methods for passive target range estimation using Doppler frequency shift mainly include: First, range estimation based on single-hydrophone Doppler frequency shift information. This method can only attempt to solve closed-form solutions for target motion parameters using methods such as the target moving to the nearest receiving point as the objective function. These models are complex, computationally intensive, and time-consuming, and require relatively accurate initial values ​​for convergence. Second, a target range and trajectory estimation method based on stationary passive sonar Doppler. This method utilizes target azimuth and spectral information extracted by passive sonar. Through transformation and derivation of the general Doppler frequency shift formula, a direct and concise computational model is proposed based on motion triangles for estimating range and motion parameters of uniformly moving linear targets. It only requires target azimuth and spectral frequency information at three observation times to estimate target range, heading, speed, and trajectory for stationary passive sonar. This method requires no iterative calculations, has a fast computation speed, and performs better with larger target azimuth and spectral frequency change rates. However, this method is only applicable to sonar on stationary platforms and not to sonar on moving platforms.

[0007] For passive sonar on moving platforms, the motion state of the target and the sonar platform is more complex than that of stationary sonar, and the number of uncontrollable factors increases significantly. Solving the distance and motion elements of the passive target is more difficult, which is also a current challenge. Summary of the Invention

[0008] This invention addresses the shortcomings of existing methods for estimating the motion parameters and range of passive targets using moving platforms. It provides a method for estimating the range and trajectory of passive sonar targets. By exploring the specific geometric relationship between the sonar and target platforms, an analytical model is derived to estimate the target's heading, speed, range, and trajectory for passive sonar on a moving platform. Using observations of the target's azimuth and spectral frequency at three time intervals, the range, heading, speed, and trajectory of the passive target are estimated. This method remains applicable even when the sonar platform is stationary, demonstrating strong versatility. Furthermore, a correction method is proposed to address the range estimation errors caused by platform motion and sound propagation delay. Through continuous observation and dynamic calculation, a target motion trajectory map similar to that of active sonar is obtained, providing richer and more important target indication information for passive target tracking, identification, and command decision-making. This invention is applicable to passive target localization in various motion situations where the sonar and target platforms are not on the same line of sight, and can also be applied to radar, electronic reconnaissance, and radio fields.

[0009] This invention provides a method for estimating the range and trajectory of a passive sonar target, comprising:

[0010] The target's trajectory relative to the sonar platform is determined by the sonar platform's single-turn discrimination method, and the sonar platform's heading and speed are confirmed during the calculation of the target's position and motion parameters.

[0011] Perform high-frequency resolution spectral analysis on the target signal;

[0012] Calculate the angle between the target position and the line connecting the sonar receiving point at the three time points; the angle is the target hull angle.

[0013] A Doppler frequency shift model of the line spectrum of the target radiated noise signal based on the sonar of a moving platform is established; the relationship between the hull angle of the sonar platform relative to the target platform and the hull angle of the target is established.

[0014] The initial hull angle and target velocity are estimated based on the target bearing and Doppler shift information and the aforementioned formula; the target distance and heading are estimated based on the initial hull angle and target velocity, and distance correction is performed.

[0015] Based on the target's speed, distance, and heading, a complete sequence of estimated target distance, heading, and speed is obtained through continuous observation, and the target trajectory is dynamically plotted.

[0016] Furthermore, the method of determining the target's movement relative to the sonar platform using a single turning discrimination method includes: setting the target's true bearing as ψ. wf Then the sonar platform's heading will be changed to H. wz =ψ wfThe sonar platform will move towards the bearing line of the detected target; when the sonar platform reaches heading H... wz =ψ wf Then, by observing the change in the target's angle relative to the sonar platform over a short period, the target's movement relative to the sonar platform is determined as follows: when the sonar platform turns right toward the target's azimuth line, i.e., the original heading H... w <ψ wf When: If the target's hull angle α changes to port, then the target's motion trajectory will be in line with the sonar platform's heading H. w Move in the same direction, otherwise in the opposite direction; when the sonar platform is turning left toward the target azimuth line, i.e., the original heading H w >ψ wf When: If the target's hull angle changes to starboard, the target's trajectory will be similar to the sonar platform's original heading H. w Movements must be in the same direction; otherwise, they must be in the opposite direction.

[0017] Furthermore, the confirmation of the sonar platform's heading and speed during the calculation of the target position and motion parameters includes: confirming that the sonar platform maintains uniform linear motion and selecting a new heading.

[0018] Furthermore, any one of the following methods is used to perform high-frequency resolution spectral analysis on the target signal: ZOOMFFT, FFT for long-duration data, MVDR high-resolution spectral estimation, or FFT with short-duration zero padding. If the target signal contains multiple line spectra, the line spectra with strong, relatively stable signals and higher frequencies within the operating frequency band are selected.

[0019] Furthermore, the calculation of the angle between the target position and the sonar receiving point at the three time points includes: at times t0, t1, and t2, the sonar platform is located at points W0, W1, and W2 respectively; at the three time points, the sonar detects signals radiated by the target at positions T0, T1, and T2 respectively; and the observed true azimuths of the target are ψ0, ψ1, ψ2 ... w0 ψ w1 ψ w2 The true azimuths of the sonar platform relative to the target platform at the three time points were calculated as ψ T0 ψ T1 ψ T2 The true bearing and heading values ​​both range from 0° to 360°.

[0020] The angles of the target on the sonar platform at the three observation times t0, t1, and t2 are as follows:

[0021] α0=|ψ w0 -H W | (1-1)

[0022] α1=|ψ w1 -H W | (1-2)

[0023] α2=|ψ w2 -H W | (1-3)

[0024] Define α0, α1, and α2 as positive values ​​in the range of 0°-180°.

[0025] Furthermore, the establishment of the Doppler frequency shift model of the target radiated noise signal line spectrum based on the sonar of the moving platform includes: assuming that the angles of the sonar platform to the target platform at the three observation times t0, t1, and t2 are β0, β1, and β2 respectively, and that the detected and selected line frequencies of the target radiated noise signal are f1(0), f1(1), and f1(2) respectively, which can be expressed as follows based on the relative motion situation:

[0026]

[0027]

[0028]

[0029] make:

[0030] c0 = c + v w cosα0, c1=c+v w cosα1,c2=c+v w cosα2 (5)

[0031] Because α0, α1, and α2 are the target hull angles obtained at three observation times, and the sonar platform velocity v w Since c0, c1, and c2 are known and observable quantities, they are known quantities.

[0032] Furthermore, the formula for establishing the relationship between the sonar platform's angle relative to the target platform and the target's angle includes:

[0033] When the target platform and the sonar platform are moving in the same direction:

[0034] β1=β0+△α1, △α1=|α0-α1| (6-1)

[0035] β2=β0+△α2, △α2=|α0-α2| (6-2)

[0036] When the target platform and the sonar platform are moving in opposite directions:

[0037] β1=β0-△α1, △α1=|α0-α1| (6-1')

[0038] β2=β0-Δα2, Δα2=|α0-α2| (6-2').

[0039] Further, estimating the initial hull angle and target velocity based on the target bearing and Doppler frequency shift information and the aforementioned relationship includes: substituting equation (5) into equations (2), (3), and (4), and then dividing equation (2) by equations (3) and (4) respectively, and recording:

[0040]

[0041]

[0042] From equation (7-1), we can obtain:

[0043]

[0044] From equation (7-2), we can obtain:

[0045]

[0046] Combining equations (8-1) and (8-2):

[0047]

[0048] make Then equation (9) becomes:

[0049]

[0050] Substituting the angle relationship (6) into equation (10) and rearranging equation (10), we can obtain the formula for solving the initial hull angle β0:

[0051]

[0052] The target velocity is estimated using equations (8-1) and (8-2) respectively:

[0053]

[0054]

[0055] Further, the step of estimating the target distance and heading based on the initial hull angle and target speed, and performing distance correction, includes:

[0056] The target distance is estimated based on the motion triangles of the sonar platform and the target:

[0057] When the sonar platform and the target platform are moving in the same direction, the target distance R2 at time t2 is:

[0058]

[0059] When the sonar platform moves in the opposite direction to the target platform, the target distance R2 at time t2 is:

[0060]

[0061] Considering the propagation delay, the corrected true distance R at the observation time can be approximately expressed as:

[0062]

[0063] The target motion heading estimation method is as follows:

[0064] First, calculate the true bearing of the sonar platform relative to the target at time t0:

[0065]

[0066] Based on the motion state and β0, the target's heading can be obtained:

[0067]

[0068] Furthermore, the step of obtaining a complete sequence of target distance, target distance, and speed estimates through continuous observation based on the target's speed, distance, and heading includes:

[0069] The complete target distance, heading, and velocity estimation sequence is obtained by the following method (1) or (2);

[0070] (1) Using the time t0 of the first motion parameter estimation as a reference, and with a certain observation time interval Δt, the three observation times of the i-th parameter estimation are obtained:

[0071]

[0072] Continuous estimation is performed based on the target azimuth and line spectrum frequency observations at times t0(i), t1(i), and t2(i);

[0073] (2) The observed values ​​of the target azimuth and its spectral frequency remain unchanged for the first two observation times. Only the acquisition time t2 of the third observation is changed for continuous observation estimation, that is:

[0074]

[0075] The passive sonar target distance and trajectory estimation method provided by this invention can achieve the following beneficial effects:

[0076] 1. This invention utilizes the observable target azimuth of passive sonar and the line spectrum frequencies obtained from LOFAR spectral analysis of the target azimuth signal. By analyzing and exploring the special geometric relationships between the sonar platform and the target platform's motion, a simplified model applicable to the estimation of the heading, speed, distance, and trajectory of all passive sonar targets is re-derived and established. Furthermore, a distance correction method is proposed to address the distance estimation errors caused by platform motion and sound propagation delay. Based on this, a complete solution for passive sonar target localization and trajectory estimation is proposed. This invention can still solve for target heading, speed, and distance parameters even when the sonar platform velocity is zero, degenerating into a stationary sonar platform. Therefore, this invention has a wider range of applications and can still be used when the sonar platform is stationary.

[0077] 2. This invention analyzes the angular relationships between the moving platforms, uncovering the relationships between the unknown hull angle variables β1 and β2 and the unknown hull angle β0, as well as the known observations α0, α1, and α2. This transforms five unknowns into three independent unknowns, allowing the target motion parameter v to be solved using the observation equations at three different times. T The initial hull angle β0 makes the previously unsolvable problem of estimating target motion parameters feasible, and greatly simplifies the algorithm model for estimating target distance and motion parameters.

[0078] 3. Based on the principles of motion geometry, this invention proposes an analytical model for estimating target distance applicable to various relative motion states. Without iterative calculations, the target distance at the third observation time can be quickly and stably solved using the target speed and initial hull angle estimate. Furthermore, to address the distance error caused by the time delay of ocean acoustic propagation, a distance correction method is proposed.

[0079] 4. This invention uses the true azimuth difference of the target observation as the input of the system, thereby obtaining the target hull angle difference (i.e., the change in hull angle) during the target motion observation process as the model parameter for calculation. This can eliminate the systematic error of the target azimuth (hull angle) observation, thereby improving the accuracy of target distance and motion parameter estimation.

[0080] 5. This invention proposes an effective method for determining the direction of target motion, laying an important foundation for the estimation of passive target motion parameters and distance based on target orientation and spectral frequency.

[0081] 6. This invention proposes principles for confirming the heading and speed of the sonar platform during the calculation of target position and motion parameters, as well as basic methods for high-resolution LOFAR spectral analysis, which helps to improve the efficiency and accuracy of target motion parameter estimation.

[0082] 7. This invention proposes a dynamic estimation method for target trajectory (azimuth, range) and speed / heading based on continuous observation of target azimuth and frequency information at three time points. It can dynamically estimate the target trajectory and motion parameters after the first parameter estimation at certain time intervals, obtaining the azimuth, range, speed, and heading at continuous observation times, and then plotting the dynamic trajectory of the moving target in polar or rectangular coordinates. This invention can achieve detection effects similar to radar (active sonar), and the data refresh rate is not limited by the transmission repetition cycle, possessing a second-level data refresh rate, greatly enriching passive target indication information, and possessing very unique technical advantages.

[0083] 8. This invention proposes a passive sonar target motion parameter, range, and trajectory estimation device, providing a complete solution for estimating target motion parameters, range, and trajectory based on the target's azimuth and single-line spectral frequency at three observation times. It is applicable to the estimation of motion parameters, range, and trajectory of passive targets with moving or stationary sonar platforms. The greater the rate of change of the target's azimuth and the rate of change of its Doppler frequency, the better the target localization, motion parameter, and trajectory estimation results. Attached Figure Description

[0084] Figure 1 This is a schematic diagram showing the relative motion and angular relationship between the receiving platform and the target in this invention, (a) moving in the same direction, (b) moving in opposite directions;

[0085] Figure 2 This is a flowchart of the calculation process of the present invention;

[0086] Figure 3 This is a flowchart illustrating the implementation of the passive sonar target distance and trajectory estimation method of the present invention.

[0087] Figure 4 shows the sonar beamforming azimuth process (a) and the LOFAR spectrum of the tracked target (b) in Example 1 of the embodiment.

[0088] Figure 5 This is a comparison chart of the observed azimuth and theoretical value of the tracked target in Example 1 of the embodiments;

[0089] Figure 6 This is a comparison chart of the observed frequency history and theoretical value of the 1100Hz line spectrum of the tracked target signal in Example 1 of the embodiment;

[0090] Figure 7 This is a comparison diagram of the target trajectory obtained by continuous dynamic estimation in Example 1 of the embodiment and the theoretical trajectory;

[0091] Figure 8 This is a comparison chart of the target distance and the theoretical distance obtained by continuous dynamic estimation in Example 1 of the embodiments;

[0092] Figure 9This is a comparison chart of the target velocity and the theoretical velocity obtained by continuous dynamic estimation in Example 1 of the embodiment.

[0093] Figure 10 This is a comparison chart of the target heading and the theoretical heading obtained by continuous dynamic estimation in Example 1 of the embodiments;

[0094] Figure 11 shows the sonar beamforming azimuth process (a) and the LOFAR spectrum of the tracked target (b) in Example 2 of the embodiment;

[0095] Figure 12 This is a comparison chart of the observed azimuth and theoretical value of the tracked target in Example 2 of the embodiment;

[0096] Figure 13 This is a comparison chart of the observed frequency and theoretical value of the 1100Hz line spectrum of the tracked target signal in Example 2 of the embodiment;

[0097] Figure 14 This is a comparison diagram of the target trajectory obtained by continuous dynamic estimation in Example 2 of the embodiment and the theoretical trajectory;

[0098] Figure 15 This is a comparison chart of the target distance and the theoretical distance obtained by continuous dynamic estimation in Example 2 of the embodiment;

[0099] Figure 16 This is a comparison chart of the target velocity and the theoretical velocity obtained by continuous dynamic estimation in Example 2 of the embodiment.

[0100] Figure 17 This is a comparison chart of the target heading and the theoretical heading obtained by continuous dynamic estimation in Example 2 of the embodiment. Detailed Implementation

[0101] To make the technical problems solved by this invention, the technical solutions adopted, and the technical effects achieved clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings, not all of them.

[0102] like Figure 2 , Figure 3 As shown, the passive sonar target range and trajectory estimation method provided in this embodiment of the invention includes:

[0103] 101. Determine the target's trajectory relative to the sonar platform using the sonar platform's single-turn discrimination method, and confirm the sonar platform's heading and speed during the calculation of the target's position and motion parameters;

[0104] Specifically, determining whether the target platform and the sonar platform are moving in the same direction (the headings of the target and the sonar platform are on the same side of the line connecting them) or in opposite directions (the headings of the target and the sonar platform are on opposite sides of the line connecting them) is the basis for solving the subsequent technology of this invention.

[0105] For passive sonar azimuth observation, although Doppler variation characteristics can be utilized, it is difficult to determine the target's trajectory solely by observing changes in azimuth and spectral frequency when the target's speed and heading are unknown. Unless a very long observation period is required for dynamic, progressive comparative analysis, this would delay strategic opportunities and is therefore undesirable. To address this, this invention proposes the following sonar platform single-turn determination method.

[0106] Let the true bearing of the target be ψ when the sonar detects the target of interest. wf Then the sonar platform's heading will be changed to H. wz =ψ wf The sonar platform will then move towards the bearing line of the detected target. When the sonar platform reaches heading H... wz =ψ wf Then, by observing the change in the target's angle equivalent to that of the sonar platform over a short period of time, the target's movement direction is determined according to the following description.

[0107] 1) When the sonar platform is turning right toward the target azimuth line, i.e., the original heading H w <ψ wf When: If the target's hull angle α changes to port, then the target's motion trajectory will be in line with the sonar platform's heading H. w Movements must be in the same direction; otherwise, they must be in the opposite direction.

[0108] 2) When the sonar platform is turning left toward the target azimuth line, i.e., the original heading H w >ψ wf When: If the target's hull angle changes to starboard, the target's trajectory will be similar to the sonar platform's original heading H. w Movements must be in the same direction; otherwise, they must be in the opposite direction.

[0109] Once the target's trajectory is determined, theoretically, as long as the sonar platform maintains uniform linear motion, the target's position and its motion parameters can be estimated. The sonar platform can return to its original course or choose a new course to ensure better target distance and parameter estimation results and accuracy.

[0110] When maritime operational conditions (e.g., maneuverability, stealth, etc.) permit, it is recommended that the sonar platform select a new course and speed to allow for a greater rate of change in the observed target azimuth and spectral frequencies. Assume the sonar platform's course in the target parameter calculation observation is H. w And a speed of v w .

[0111] 102. Perform high-frequency resolution spectral analysis on the target signal;

[0112] Specifically, to ensure the accuracy of target distance and motion parameters, high-frequency resolution spectral analysis methods are required. These can include: ZOOMFFT, FFT for long-duration data, MVDR high-resolution spectral estimation with short-duration zero-padding FFT, or other high-frequency resolution spectral analysis methods.

[0113] If the target signal contains multiple line spectra, then line spectra with strong, relatively stable signals and higher frequencies within the operating frequency band should be selected.

[0114] 103. Calculate the angle between the target position and the line connecting the sonar receiving point at the three time points. The angle is the target's hull angle.

[0115] Specifically, at times t0, t1, and t2, the sonar platform is located at points W0, W1, and W2, respectively. At these three times, the sonar detects signals radiated by the target at positions T0, T1, and T2, respectively. The observed true azimuths of the target are ψ. w0 ψ w1 ψ w2 The true azimuths of the sonar platform relative to the target platform at the three time points were calculated as ψ T0 ψ T1 ψ T2 The true bearing and heading values ​​both range from 0° to 360°.

[0116] The angles of the target on the sonar platform at the three observation times t0, t1, and t2 are as follows:

[0117] α0=|ψ w0 -H W | (1-1)

[0118] α1=|ψ w1 -H W | (1-2)

[0119] α2=|ψ w2 -H W | (1-3)

[0120] Define α0, α1, and α2 as positive values ​​in the range of 0°-180°.

[0121] 104. Establish a Doppler frequency shift model for the line spectrum of target radiated noise signal based on a moving platform sonar; establish the relationship between the sonar platform's relative angle to the target platform and the target's angle.

[0122] Specifically, let the angles of the sonar platform relative to the target platform at the three observation times t0, t1, and t2 be β0, β1, and β2, respectively. Let the frequency of a certain line spectrum of the target radiated noise signal detected and selected be f1(0), f1(1), and f1(2), respectively. Based on the relative motion situation, this can be expressed as:

[0123]

[0124]

[0125]

[0126] make:

[0127] c0 = c + v w cosα0, c1=c+v w cosα1,c2=c+v w cosα2 (5)

[0128] Because α0, α1, and α2 are the target hull angles obtained at three observation times, and the sonar platform velocity v w Since c0, c1, and c2 are known and observable quantities, they are known quantities.

[0129] according to Figure 1 The diagram shows the motion of the sonar platform and the target platform. At the three observation times t0, t1, and t2, the sonar platform is located at points W0, W1, and W2, respectively, and the hull angles of the sonar platform relative to the target platform are β0, β1, and β2, respectively. Two sets of auxiliary lines (thick and thin) parallel to the line connecting W0 and T0 are drawn at points W1, W2, T1, and T2, respectively. The following angular relationships can be clearly obtained through these auxiliary lines.

[0130] 1) When the target platform and the sonar platform are moving in the same direction:

[0131] β1=β0+△α1, △α1=|α0-α1| (6-1)

[0132] β2=β0+△α2, △α2=|α0-α2| (6-2)

[0133] 2) When the target platform and the sonar platform are moving in opposite directions:

[0134] β1=β0-△α1, △α1=|α0-α1| (6-1')

[0135] β2=β0-△α2, △α2=|α0-α2| (6-2')

[0136] 105. Estimate the initial hull angle and target velocity based on the target bearing and Doppler frequency shift information and the aforementioned formula; estimate the target distance and heading based on the initial hull angle and target velocity, and perform distance correction;

[0137] Specifically, substitute equation (5) into equations (2), (3), and (4), then divide equation (2) by equations (3) and (4) respectively, and record:

[0138]

[0139]

[0140] From equation (7-1), we can obtain:

[0141]

[0142] From equation (7-2), we can obtain:

[0143]

[0144] Combining equations (8-1) and (8-2):

[0145]

[0146] make Then equation (9) becomes:

[0147]

[0148] Substituting the angle relationship (6) into equation (10) and rearranging equation (10), we can obtain the formula for solving the initial hull angle β0:

[0149]

[0150] From equations (8-1) and (8-2), the velocity estimation expressions are obtained respectively:

[0151]

[0152]

[0153] Either one is sufficient.

[0154] The target distance estimation method is as follows:

[0155] according to Figure 1The diagram showing the relative motion between the sonar platform and the target platform includes auxiliary lines perpendicular to the line connecting W0 and T0 at points W2 and T2, respectively. When the sonar platform and the target platform are moving in opposite directions, the auxiliary line perpendicular to the line connecting W0 and T0 at point W2 is extended to a line parallel to the line connecting W0 and T0 at point T2. Using these auxiliary lines, the formula for calculating the target distance R2 at observation time t2 can be easily obtained. When the sonar platform and the target platform are moving in the same direction, the target distance R2 at time t2 is:

[0156]

[0157] When the sonar platform moves in the opposite direction to the target platform, the target distance R2 at time t2 is:

[0158]

[0159] Because the target is moving, when the target signal is observed at time t2, the target has actually moved to position T2'. Therefore, the actual target distance at time t2 should be R = |W2T2'|, because W... i T i With W i T i The angle between the lines connecting '(i=0,1,2) is very small; therefore, the true distance R at the observation time can be approximated as:

[0160]

[0161] The target motion heading estimation method is as follows:

[0162] First, calculate the true bearing of the sonar platform relative to the target at time t0:

[0163]

[0164] Based on the motion state and β0, the target's heading can be obtained:

[0165]

[0166] 106. Based on the target's speed, distance, and heading, obtain a complete sequence of estimated target distance, heading, and speed using continuous observation, and dynamically plot the target trajectory.

[0167] Specifically, based on the target's bearing and spectral frequency at three observation times, the target distance R and speed v are obtained. T Heading H T Assuming the target maintains uniform linear motion, then through continuous observation, following steps 102-105, we can obtain {R(t)}. i ), H T (t i), v T (t i The estimated sequence (where i represents the order of range, heading, and speed estimates) is then used to obtain the complete target range, heading, and speed estimation sequence. There are two implementation methods:

[0168] 1) Using the time t0 of the first motion parameter estimation as a reference, and with a certain observation time interval Δt, obtain the three observation times for the i-th parameter estimation:

[0169]

[0170] Continuous estimation is performed based on the target azimuth and line spectrum frequency observations at times t0(i), t1(i), and t2(i).

[0171] 2) The first two observation times and the observed values ​​of the target azimuth and its spectral frequency remain unchanged. Only the acquisition time t2 of the third observation is changed for continuous observation estimation, that is:

[0172]

[0173] 3) Based on the observation time of method (1) or method (2), obtain the target azimuth and line spectrum frequency at three times t0(i), t1(i), and t2(i). Then, follow implementation steps 102-105 to obtain {R(t i ), H T (t i ), v T (t i Estimate the sequence.

[0174] Starting from the third moment, the target's azimuth θ(t) can be observed at certain time intervals. i ), distance R(t) i This allows us to draw the dynamic trajectory of the target in polar coordinates with the stationary observation point O as the pole; alternatively, we can convert it to a rectangular coordinate system for drawing.

[0175] Simulation example:

[0176] Example Background: Suppose an underwater passive sonar is located at point O, and the speed of sound in seawater is c = 1500 m / s. Target T travels at a velocity v. T Heading H T Motion. At times t0, t1, and t2, the target is located at positions T0, T1, and T2, respectively. The fixed sonar detects the target signal and measures the true azimuth as ψ0, ψ1, and ψ2, respectively. The angles (angles of the receiving point) between the target's heading and the line connecting the receiving array position O are β0, β1, and β2, respectively. The continuous dynamic trajectory is estimated using equation (18).

[0177] Application Example 1

[0178] Assume the initial time for calculating the target's motion parameters is t=0, the target's heading is 90°, its speed is 18 knots, its depth is 5 meters, its initial distance is 10 km, and its initial true bearing is 40 degrees. The target signal is generated according to a ship radiated noise signal model (simulating continuous spectrum, line spectrum, and modulation spectrum characteristics), the target radiated signal source level is 170 dB, and the simulation includes four line spectra (1100 Hz, 1300 Hz, 1500 Hz, and 1700 Hz). This application example uses the line spectrum with a real frequency of 1100 Hz for target distance and motion parameter estimation.

[0179] The sonar is a uniform 48-element linear array with an element spacing of 0.5m. The sonar platform operates at a speed of 6 knots with a heading of 0° and a draft of 5 meters. The marine environment noise level is 100dB, the sea area is at a depth of 150m with a flat seabed, the sound speed in the sea is c = 1500m / s, and the sonar receiving array depth is 100m. The underwater acoustic channel was calculated using the Bellhop model.

[0180] The calculation times in this example are t0 = 10 seconds, t1 = 150 seconds, and t2 = 280 seconds. The subsequent time interval for dynamic trajectory estimation is Δt = 10 seconds.

[0181] The target azimuth history obtained after sonar beamforming is shown in Figure 4(a), and the LOFAR spectrum of the target tracking azimuth signal is shown in Figure 4(b).

[0182] Figure 5 This example compares the observed azimuth and theoretical value of the tracked target.

[0183] Figure 6 This example compares the observed azimuth of the tracked target with the theoretical value. For the tracked target azimuth signal, an FFT (i.e., frequency resolution of 0.1Hz) is performed for a data length of 10 seconds each time. The maximum value is taken as the observed frequency of the line spectrum, and the frequency-time history of the line spectrum obtained by line spectrum tracking is plotted.

[0184] Figure 7 The target trajectory obtained by continuous dynamic estimation in this example is compared with the theoretical trajectory: the left figure is the target trajectory in polar coordinates, and the right figure is the target trajectory in rectangular coordinates.

[0185] Figure 8 This example compares the target distance obtained by continuous dynamic estimation with the theoretical distance.

[0186] Figure 9 This example compares the target velocity obtained by continuous dynamic estimation with the theoretical velocity.

[0187] Figure 10 This example compares the target heading obtained through continuous dynamic estimation with the theoretical heading.

[0188] Application Example 2:

[0189] The simulation begins at time t=0, with an initial target distance of 10km, an initial true azimuth of 40 degrees, a target heading of 210°, and a speed of 18 knots. The marine environment, sonar parameters, receiving depth, target depth, and simulated target signal parameters are the same as in Example 1. This application example uses a line spectrum with a real frequency of 1100Hz for target distance and motion parameter estimation.

[0190] The target azimuth history obtained after sonar beamforming is shown in Figure 11(a), and the LOFAR spectrum of the target tracking azimuth signal is shown in Figure 11(b).

[0191] The calculation times in this example are t0 = 10 seconds, t1 = 150 seconds, and t2 = 280 seconds. The subsequent time interval for dynamic trajectory estimation is Δt = 10 seconds.

[0192] Figure 12 This example compares the observed azimuth and theoretical value of the tracked target.

[0193] Figure 13 This example compares the observed azimuth of the tracked target with the theoretical value. For the tracked target azimuth signal, an FFT (i.e., frequency resolution of 0.1Hz) is performed for a data length of 10 seconds each time. The maximum value is taken as the observed frequency of the line spectrum, and the frequency-time history of the line spectrum obtained by line spectrum tracking is plotted.

[0194] Figure 14 The target trajectory obtained by continuous dynamic estimation in this example is compared with the theoretical trajectory: the left figure is the target trajectory in polar coordinates, and the right figure is the target trajectory in rectangular coordinates.

[0195] Figure 15 This example compares the target distance obtained by continuous dynamic estimation with the theoretical distance.

[0196] Figure 16 This example compares the target velocity obtained by continuous dynamic estimation with the theoretical velocity.

[0197] Figure 17 This example compares the target heading obtained through continuous dynamic estimation with the theoretical heading.

[0198] As can be seen, the estimated results of the target speed, heading and distance are consistent with the theoretical values ​​set in the simulation background, and the error is within the allowable range.

[0199] In the two target motion scenarios described above, the changes in line spectrum Doppler frequency shift caused by target motion are very small. This invention can estimate target distance, speed, heading, and trajectory with high accuracy in a short time. Furthermore, the accuracy of each estimated parameter and the trajectory points become increasingly precise with prolonged observation time. The greater the rate of change of the target's azimuth and Doppler frequency, the better the effect of this invention in target localization and motion parameter and trajectory estimation, demonstrating significant practical and widespread application value.

[0200] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications to the technical solutions described in the foregoing embodiments, or equivalent substitutions for some or all of the technical features, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for passive sonar target range and motion trajectory estimation, characterized in that, The method comprises: judging the moving direction of the target relative to the sonar platform by one-time turning discrimination method of the sonar platform, and confirming the course and speed of the sonar platform in the process of solving the position and motion parameters of the target; performing spectrum analysis on the target signal with high frequency resolution; calculating the included angle between the target position and the connecting line of the sonar receiving point at three time points, which is the target bearing angle; establishing a model of Doppler frequency shift of the target radiated noise signal spectrum based on the sonar of the moving platform; and establishing a relationship between the sonar platform relative to the target platform bearing angle and the target bearing angle; estimating the initial bearing angle and the target motion speed according to the target bearing and Doppler shift information and the relationship; estimating the target distance and motion course according to the initial bearing angle and the target motion speed, and performing distance correction; obtaining a complete target distance, motion course and speed estimation sequence by continuous observation method according to the target motion speed, target distance and motion course, and dynamically drawing the target trajectory.

2. The method of claim 1, wherein, The judgment of the moving direction of the target relative to the sonar platform by one-time turning discrimination method of the sonar platform comprises: Set the target true bearing as ψ wf Then change the sonar platform course to H wz = ψ wf That is, the sonar platform moves towards the bearing line of the discovered target; when the sonar platform reaches the course H wz = ψ wf After a short time of observing the target, the change of the sonar platform beam angle is equivalent to the change of the target relative to the sonar platform, and the moving direction of the target relative to the sonar platform is determined according to the following manner: When the sonar platform is turning to starboard to the target bearing line, i.e. the original heading H w <ψ wf If the target bearing angle α changes to port, the target motion heading moves in the same direction as the sonar platform heading H w , otherwise in the opposite direction. When the sonar platform is turning to port to the target bearing line, i.e. the original heading H w >ψ wf If the target bearing changes to starboard, the target motion is moving in the same direction as the sonar platform original heading H w , otherwise in the opposite direction.

3. The method of claim 2, wherein, The confirmation of the course and speed of the sonar platform in the process of solving the position and motion parameters of the target comprises: confirming that the sonar platform keeps uniform linear motion, and selecting a new course that is favorable for observation and solution.

4. The method of claim 3, wherein, Any one of ZOOMFFT, long-time data FFT, MVDR high-resolution spectrum estimation and short-time zero-padding FFT method is adopted to perform spectrum analysis on the target signal with high frequency resolution; if the target signal contains multiple line spectra, a line spectrum signal with high strength, relatively stable and higher frequency in the working frequency band is selected.

5. The method of claim 4, wherein, The calculation of the included angle between the target position and the connecting line of the sonar receiving point at three time points comprises: The sonar platform is located at W0, W1, W2 points at t0, t1, t2 moments respectively, and the sonar detects signals radiated by the target located at T0, T1, T2 position points respectively at three moments, and the true bearings of the observed target are ψ w0 , ψ w1 , ψ w2 respectively, and the true bearings of the sonar platform relative to the target platform at three moments are ψ T0 , ψ T1 , ψ T2 respectively; the true bearings and the headings are both in the range of 0°-360°. The target bearing angles of the target located at the sonar platform at three observation time points t0, t1 and t2 are respectively: a0= | ψ w0 - H W | (1-1) a1 = | ψ w1 - H W | (1-2) a2= | ψ w2 - H W | (1-3) α0, α1 and α2 are defined as positive values in the range of 0°-180°.

6. The method of claim 5, wherein, The establishment of the model of Doppler frequency shift of the target radiated noise signal spectrum based on the sonar of the moving platform comprises: the sonar platform bearing angles of the sonar platform located at the target platform at three observation time points t0, t1 and t2 are respectively β0, β1 and β2, and the frequencies of some line spectra of the target radiated noise signal detected and selected are respectively f1(0), f1(1) and f1(2), which are expressed as: Let: c0= c + v w cos a0, c1= c + v w cos a1, c2= c + v w cos a2 (5) Because a0, a1, a2 are target bearing angles obtained at three observation times, and the sonar platform velocity v w Given that c0, c1, c2 are observable known quantities.

7. The method of claim 6, wherein, The establishment of the relationship between the sonar platform relative to the target platform bearing angle and the target bearing angle comprises: when the target platform and the sonar platform move in the same direction: β1=β0+Δα1, Δα1=|α0-α1| (6-1) β2=β0+Δα2, Δα2=|α0-α2| (6-2) when the target platform and the sonar platform move in opposite directions: β1=β0-Δα1, Δα1=|α0-α1| (6-1') β2=β0-Δα2, Δα2=|α0-α2| (6-2').

8. The method of claim 7, wherein, The estimation of the initial bearing angle and the target motion speed according to the target bearing and Doppler shift information and the relationship comprises: substitute equation (5) into equations (2), (3) and (4), then divide equation (2) by equations (3) and (4) respectively, and record: from equation (7-1), we can get: from equation (7-2), we can get: Combining (8-1) and (8-2) formula: Let Then equation (9) becomes: B1cosβ0-cosβ1=B3(B2cosβ0-cosβ2) (10) Again, the angle relationship (6) into (10) formula, (10) formula can be obtained by sorting the initial side angle β0 solving formula: By (8-1), (8-2) formula respectively realize target speed estimation:

9. The method of claim 8, wherein, The initial side angle and target motion speed according to the target distance and motion heading, and distance correction, comprising: The target distance is estimated according to the sonar platform motion triangle and target motion triangle: When the sonar platform and target platform in the same direction, t2 time target distance R2 is: When the sonar platform and target platform in the opposite direction, t2 time target distance R2 is: Considering the propagation delay, the real distance R of the observation time is obtained by correction: The target motion heading estimation method is: First, calculate the true bearing of the sonar platform relative to the target at t0 time: Then, according to the motion situation and β0, the target motion heading can be obtained:

10. The method of claim 9, wherein, The complete target distance, motion heading and speed estimation sequence is obtained by continuous observation method according to the target motion speed, target distance and motion heading, comprising: The complete target distance, motion heading and speed estimation sequence is obtained by the following first or second method; First: take t0 time of the first motion parameter estimation as the benchmark, take the observation time interval Δt, get the three observation time of the i-th parameter estimation: According to the target bearing and line spectrum frequency observation at t0(i), t1(i), t2(i) time, continuous estimation is carried out; Second: the first two observation time and target bearing and its line spectrum frequency observation value is unchanged, only change the acquisition time t2 of the third observation, continuous observation estimation, namely:

Images