A target range and trajectory estimation method based on stationary passive sonar Doppler

Abstract

The present invention relates to the field of underwater acoustic engineering technology and provides a method for estimating target distance and trajectory based on stationary passive sonar Doppler. The method comprises: establishing a simple model for estimating distance and motion parameters for a uniform linear motion target by transforming and deriving a general formula for Doppler frequency shift and establishing a target motion triangle. The method only requires observations of the target's azimuth and single line spectrum frequency at three moments at a certain time interval to estimate the target's distance, course, and speed. Through continuous observation and dynamic calculation, a target motion track diagram similar to that of radar or active sonar is obtained. Furthermore, the data refresh rate of the target position point can be arbitrarily set according to the speed of position change, resulting in a higher data refresh rate than that of active sonar. The method can provide richer and more important target indication information for passive target tracking, identification, and command decision-making, and can also be applied to radar, electronic reconnaissance, radio, and other fields.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater acoustic engineering, and in particular to a target distance and trajectory estimation method based on stationary passive sonar Doppler. Background Art

[0002] Fixed-position (stationary) sonar platforms are one of the main forms of passive sonar. The sonar target's direction, range, motion parameters, and trajectory are crucial elements of target information. They are essential for target situation assessment, threat estimation, and command decision-making, and are also a key area of ​​research in underwater acoustic signal and information processing. Typically, passive sonar can only observe the target's direction (bow angle) and cannot measure the target's range or trajectory. The core of passive sonar target positioning is distance estimation. The main methods of passive target distance estimation are: the matching field method based on prior information of the ocean environment, which is a method of pre-calculating the sound field of the observed sea area according to a certain azimuth, distance and depth grid, and matching the calculated copy sound field with the actual measured sound field to estimate the distance and depth position of the target. It requires relatively accurate ocean acoustic environment information and has a relatively large amount of calculation; the three-subarray ranging method uses three subarrays to estimate azimuth information and uses azimuth method or time difference method to estimate distance. Its accuracy is related to the subarray spacing and target distance, and is generally suitable for situations where the target distance is relatively close; the distance estimation method based on shallow sea waveguide invariants uses the interference fringes generated by target motion in the LOFAR spectrum to estimate the target distance by obtaining the slope of the fringes. In order to obtain a more accurate slope, long-term observation is required. This method is mainly suitable for shallow seas and situations where the target distance is relatively close. Target motion analysis (TMA) is a classic method for estimating the range and motion parameters of moving targets. It is a bearing-only target motion parameter estimation method. It utilizes the time-series information of the target's bearing observed during the motion of a passive sonar platform to establish measurement equations and target motion state equations. Using techniques such as least squares, Kalman filtering, and insensitive filtering, target position and motion parameter estimation is performed. This method requires the sonar platform to be in motion and the target state to be observable. However, when both the sonar platform and the target are in uniform linear motion, the target state is unobservable. To improve observability, the sonar platform must perform at least one turning maneuver during the target motion parameter calculation. In practical applications, this method suffers from the following major issues: the sonar platform requires maneuvering, the computation time is long (typically 10-30 minutes for underwater targets), and the algorithm is prone to divergence or even unsolvable, which seriously affects its effectiveness. Furthermore, this method is not suitable for stationary sonar platforms.

[0003] Target positioning based on Doppler shift characteristics has widespread applications in radar, radio communications, radio reconnaissance, and other fields. Existing methods use the Doppler shift within a specific observation timeframe for positioning or velocity estimation. Because radar targets (especially aerial targets) move quickly and radar and radio communications have very high frequencies, Doppler shift is very pronounced and the Doppler shift within a specific observation timeframe is relatively large. Consequently, these methods have been relatively successful in radar, communications, and reconnaissance. However, underwater targets (especially those moving quietly underwater) move slowly and passive sonar operates at a low frequency. Under these circumstances, the Doppler shift of the signal within a specific timeframe is very small. Therefore, conventional target velocity estimation or positioning methods based on Doppler shift characteristics are unstable, take a long time to converge, or even fail to converge, and thus fail to meet the requirements for underwater acoustic target positioning.

[0004] Currently, for stationary underwater acoustic systems, the main methods for passive target distance estimation using Doppler shift are: Distance estimation based on Doppler shift information from a single hydrophone. This method can only estimate the target distance when the target moves to the closest point of reception (CPA), making it suitable for close-range targets and inapplicable when the target moves away from the reception point. To address the problem of requiring the closest point to estimate distance, a direct Doppler positioning method for underwater targets has emerged. This method measures the line spectrum frequency multiple times and uses the ratio of the two previous frequency measurements to infer the target's speed and distance. Although this method can estimate the target distance before the target reaches the CPA point, it is only applicable when the target is relatively close and moving close to the reception point, and has significant application limitations. Passive directional acoustic buoys also use a similar CPA estimation method, which can only estimate the distance to the nearest point of the target. Later, another solution emerged, which is to establish measurement equations and state equations related to the target motion parameters and frequency. Through methods such as least squares and Kalman filtering, and using maximum likelihood functions as objective functions, attempts to solve the closed-form solution of the target motion parameters. This type of model is complex, the calculation process is complex, the calculation time is long, and it requires a relatively accurate initial value to solve, otherwise it will be difficult to converge. Summary of the Invention

[0005] The present invention primarily addresses the above-mentioned technical problems and proposes a target range and trajectory estimation method based on stationary passive sonar Doppler. Utilizing target azimuth and line spectrum frequency information obtained by passive sonar, and through the transformation and derivation of the general formula for Doppler frequency shift and the principle of motion geometry, a direct and concise calculation model for estimating the distance and motion parameters of a uniformly moving linear target is established. Only target azimuth and single line spectrum frequency observations at three moments at a certain time interval are required to rapidly estimate the target range, heading, and speed. A target motion track (polar coordinate or rectangular coordinate) diagram similar to that of radar (or active sonar) is obtained through continuous observation and dynamic calculation. Furthermore, the method has a higher data refresh rate than active sonar (not limited by the transmission repetition period), thus providing richer and more important target indication information for target tracking, identification, and command decision-making.

[0006] The present invention provides a target distance and trajectory estimation method based on stationary passive sonar Doppler, comprising:

[0007] S1. Setting simulation motion status;

[0008] S2. Calculate two angles between the target position and the line connecting the sonar receiving points based on the target true azimuth at the three observation times, where the two angles are the target azimuth changes;

[0009] S3. Establishing a Doppler frequency shift model for the sonar signal of a stationary platform to obtain the relationship between the signal line spectrum frequency at the three observation times and the target azimuth, target motion speed, and target side angle;

[0010] S4. Establishing a relationship between the target's subsequent broadside angle, the target's initial broadside angle, and the azimuth change based on a motion triangulation geometric relationship, obtaining an improved Doppler model for estimating motion parameters of a stationary sonar target, and calculating the inverse of the signal line spectrum frequency at the three observation moments;

[0011] S5. Calculate two differences based on the reciprocals of the line spectrum frequencies at the three observation moments, then calculate the ratio of the two differences to calculate the initial side angle; calculate the target motion speed based on the reciprocals of the signal line spectrum frequencies at the three observation moments and the initial side angle;

[0012] S6. Calculate the target distance at the third observation moment based on the target movement speed and initial broadside angle and a target distance estimation model established based on the motion triangle; calculate the target heading based on the true bearing line of the sonar observation platform relative to the target and the initial broadside angle;

[0013] S7. Repeat the updating of the three observation moments according to the update step size set according to the data refresh rate requirement, and execute steps S2 to S6 to form a target distance, target heading and target motion speed estimation sequence, and draw a target dynamic trajectory diagram based on the output estimation sequence.

[0014] Furthermore, the setting of the simulated motion situation includes: setting the sonar receiving array to be stationary at point O, and the target T to move at a speed v T , initial side angle β0, according to the heading H T Motion; at t0, t1, and t2, the target is located at T0, T1, and T2 respectively, radiating its noise. The stationary sonar detects the target radiation noise signal and measures the true bearing respectively as ψ0, ψ1, and ψ2. The angle between the target heading and the line connecting the receiving array position point O, that is, the side angle of the receiving point relative to the target, is β0, β1, and β2 respectively.

[0015] Furthermore, the step S2 includes:

[0016] α0=|ψ0-ψ1| (1)

[0017] α1=|ψ2-ψ1| (2).

[0018] Furthermore, the step S3 includes: setting the moving speeds of the moving target platform and the sonar receiving platform to be v respectively. T and v w , and the target signal has a line spectrum, and the original frequency of the line spectrum is f1, then according to the relative motion Doppler principle, the frequency after Doppler shift is:

[0019]

[0020] Assume that at three observation times t i (i=0,1,2.), the line spectrum frequency of the measured signal is:

[0021]

[0022] where α i and β i t i The relative side angle between the sonar platform and the target platform at any moment;

[0023] Because the receiving platform does not move, that is, v w =0, then:

[0024]

[0025] Furthermore, the step S4 includes: taking the reciprocal of both sides of formula (5) to obtain:

[0026]

[0027] Introduce the reciprocal variable: i The reciprocal of the target signal line spectrum frequency observed at the moment and the unknown true frequency is:

[0028]

[0029] Then formula (6) can be expressed as:

[0030]

[0031] Among them, according to the motion triangle geometric relationship diagram, there are:

[0032] β1=α0+β0 (9)

[0033] β2=α1+β1=α1+α0+β0 (10)

[0034] Formula (8) is an improved model of Doppler frequency shift expressed by the inverse of frequency.

[0035] Furthermore, step S5 includes:

[0036] Assume that at the three observation times t0, t1, and t2, the frequencies of the line spectrum are detected as f1(0), f1(1), and f1(2), respectively, and their reciprocals are The difference between the reciprocals of the line spectrum frequencies detected at the three moments t0, t1, and t2 is obtained from formula (6):

[0037]

[0038]

[0039] Divide (11) by (12) and introduce the frequency change ratio:

[0040]

[0041] Then we have:

[0042] cosβ0-cos(α0+β0)=A[cosβ0-cos(α0+α1+β0)] (14)

[0043] According to the trigonometric formula cos(α+β)=cosαcosβ-sinαsinβ, we can deduce from formula (14):

[0044]

[0045] According to formula (8), the inverse of the detection line spectrum frequency at time t0 is:

[0046]

[0047] The inverse of the true line spectrum frequency can be obtained as:

[0048]

[0049] Taking the reciprocal of formula (17-1) gives the true frequency of the line spectrum:

[0050]

[0051] The inverse of the line spectrum frequency detected at time t2 is:

[0052]

[0053] Substitute (17) into (18):

[0054]

[0055] Arranging (19) yields:

[0056]

[0057] By rearranging formula (20), we can get the target motion speed:

[0058]

[0059] Where, It is the reciprocal of the line spectrum frequencies f1(0) and f1(2) detected at time t0 and t2. α0, α1, and β0 are calculated by equations (1), (2), and (15), respectively.

[0060] Furthermore, the step S6 includes: according to the target initial side angle β0 and the target speed v T , using geometric principles to obtain the target distance at time t2:

[0061]

[0062] Calculate the true bearing line of the sonar observation platform relative to the target:

[0063]

[0064] According to the initial side angle β0 of the sonar observation platform relative to the moving target, the target's heading is calculated by formula (24):

[0065]

[0066] Furthermore, the formation of the target distance, target heading and target motion speed estimation sequence includes: taking the time t0 of the first motion parameter estimation as a reference, and obtaining three observation times of the i-th parameter estimation at a certain observation time interval Δt:

[0067]

[0068] Continuously estimate the target direction and line spectrum frequency observations at t0(i), t1(i), and t2(i);

[0069] Obtain the target direction and line spectrum frequency at the three moments t0(i), t1(i), and t2(i), and follow steps S2 to S6 to obtain {R(t i ), H T (t i ), v T (t i )}Estimated sequence.

[0070] Furthermore, the formation of the target distance, target heading and target motion speed estimation sequence includes: the observation values ​​of the first two observation moments and the target azimuth and its line spectrum frequency among the three observation moments remain unchanged, and only the acquisition time t2 of the third observation value is changed for continuous observation and estimation, that is:

[0071]

[0072] Obtain the target direction and line spectrum frequency at the three moments t0(i), t1(i), and t2(i), and follow steps S2 to S6 to obtain {R(t i ), H T (t i ), v T (t i )}Estimated sequence.

[0073] Furthermore, the target dynamic trajectory diagram is drawn according to the output estimation sequence, including: starting from the third moment, observing the target orientation θ (t i ), distance R(t i ), draw the target dynamic trajectory diagram in polar coordinates with the stationary observation point O as the pole, and then convert it to a rectangular coordinate system to draw the target motion trajectory diagram in the rectangular coordinate system.

[0074] The present invention provides a method for estimating target distance and trajectory based on stationary passive sonar Doppler. By deriving and transforming the general formula for Doppler frequency shift, a direct and concise calculation model is established for estimating the distance and motion parameters of uniform linear motion targets, without the need for iterative calculations. Using the target's azimuth and single line spectrum frequency observations at three time intervals, the target's distance, course, and speed are rapidly estimated. Furthermore, through continuous observation and dynamic calculation, a target motion track (polar or rectangular coordinate) diagram similar to that of radar (or active sonar) is obtained, with a higher data refresh rate than active sonar (not limited by the transmission repetition period). The present invention is not applicable to stationary targets or targets moving toward or away from the sonar position, but is applicable in all other situations. Furthermore, the greater the target azimuth change rate and Doppler frequency change rate, the earlier the passive target positioning and motion trajectory estimation are achieved, and the higher the estimation accuracy. The present invention can provide richer and more important target indication information for passive target tracking, identification, and command decision-making, and can also be applied to radar, electronic reconnaissance, radio, and other fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 This is a flow chart of the target distance and trajectory estimation method based on stationary passive sonar Doppler of the present invention;

[0076] Figure 2 It is a calculation flow chart of the present invention;

[0077] Figure 3 It is a relative situation diagram of the stationary sonar platform and the target movement in the present invention;

[0078] Figure 4 This is the sonar beamforming azimuth process diagram in simulation example 1;

[0079] Figure 5 This is the LOFAR spectrum of the tracked target in simulation example 1;

[0080] Figure 6 This is a comparison chart of the observed azimuth and theoretical value of the tracked target in simulation example 1;

[0081] Figure 7 This is a comparison chart of the observed frequency history of the 799Hz line spectrum of the tracked target signal in simulation example 1 and its theoretical value;

[0082] Figure 8 This is a comparison diagram of the target motion trajectory obtained by continuous dynamic estimation in simulation example 1 and the theoretical trajectory (the left figure is the comparison diagram in polar coordinates, and the right figure is the comparison diagram in rectangular coordinates);

[0083] Figure 9 This is a comparison chart of the target distance obtained by continuous dynamic estimation and the theoretical distance in simulation example 1;

[0084] Figure 10 This is a comparison chart of the target speed obtained by continuous dynamic estimation and the theoretical speed in simulation example 1;

[0085] Figure 11 This is a comparison diagram between the target heading obtained by continuous dynamic estimation and the theoretical heading in simulation example 1;

[0086] Figure 12 This is the sonar beamforming azimuth process diagram in simulation example 2;

[0087] Figure 13 This is the LOFAR spectrum of the tracked target in simulation example 2;

[0088] Figure 14 This is a comparison chart of the observed azimuth of the tracked target in simulation example 2 and the theoretical value;

[0089] Figure 15 This is a comparison chart of the observed frequency of the 799Hz line spectrum of the tracked target signal in simulation example 2 and its theoretical value;

[0090] Figure 16 This is a comparison diagram of the target motion trajectory obtained by continuous dynamic estimation in simulation example 2 and the theoretical trajectory (the left figure is the comparison diagram in polar coordinates, and the right figure is the comparison diagram in rectangular coordinates);

[0091] Figure 17 This is a comparison chart of the target distance obtained by continuous dynamic estimation and the theoretical distance in simulation example 2;

[0092] Figure 18 This is a comparison chart of the target speed obtained by continuous dynamic estimation and the theoretical speed in simulation example 2;

[0093] Figure 19 This is a comparison chart between the target heading obtained by continuous dynamic estimation and the theoretical heading in simulation example 2. DETAILED DESCRIPTION

[0094] To make the technical problems solved, the technical solutions adopted, and the technical effects achieved by the present invention more clearly apparent, the present invention is 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 present invention and are not intended to limit the present invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions relevant to the present invention, rather than all of the contents.

[0095] like Figure 1 、 Figure 2 As shown, the target distance and trajectory estimation method based on stationary passive sonar Doppler provided by the embodiment of the present invention includes:

[0096] S1. Setting simulation motion status;

[0097] Specifically, if Figure 3 As shown in the figure, the underwater passive sonar is set to be stationary at point O, and the speed of sound in seawater is c = 1500m / s. The target T moves at a speed v T , heading H T At 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 bearings ψ0, ψ1, and ψ2, respectively. The angles between the target heading and the line connecting the receiving array position O (the beam angle of the receiving point) are β0, β1, and β2, respectively.

[0098] S2. Calculate two angles between the target position and the line connecting the sonar receiving points based on the target true azimuth at the three observation times. The two angles are the target azimuth change.

[0099] Specifically, the two angles between the target position and the line connecting the sonar receiving point at the three observation moments are calculated by equations (1)-(2);

[0100] α0=|ψ0-ψ1| (1)

[0101] α1=|ψ2-ψ1| (2).

[0102] S3. Establish a Doppler frequency shift model for the sonar signal from a stationary platform to obtain the relationship between the signal line spectrum frequency and the target azimuth (change), target speed, and target side angle at three observation times;

[0103] Specifically, the moving speeds of the moving target platform and the sonar receiving platform are set to v T and v w , and the target signal has a line spectrum, and the frequency of the original line spectrum is f1, then according to the relative motion Doppler principle, the frequency after Doppler shift is:

[0104]

[0105] At the observation time t i (i=0,1,2.), the line spectrum frequency of the measured signal is:

[0106]

[0107] where α i and β i t i The relative side angle between the sonar platform and the target platform at any moment;

[0108] Because the receiving platform does not move, that is, v w =0, then:

[0109]

[0110] S4. Establishing a relationship between the target's subsequent broadside angle, the target's initial broadside angle, and the azimuth change based on the motion triangulation geometric relationship, obtaining an improved Doppler model that can be used to estimate motion parameters of stationary sonar targets, and calculating the reciprocals of the signal line spectrum frequencies at the three observation moments;

[0111] Specifically, taking the inverse of both sides of formula (5), we get:

[0112]

[0113] Introduce the reciprocal variable: i The reciprocal of the target signal line spectrum frequency observed at the moment and the unknown true frequency is:

[0114]

[0115] Then formula (6) can be expressed as:

[0116]

[0117] Among them, according to the motion triangle geometric relationship diagram, there are:

[0118] β1=α0+β0 (9)

[0119] β2=α1+β1=α1+α0+β0 (10)

[0120] Formula (8) is an improved model of Doppler frequency shift expressed by the inverse of frequency.

[0121] S5. Calculate two differences based on the reciprocals of the line spectrum frequencies at the three observation moments, then calculate the ratio of the two differences to calculate the initial side angle; calculate the target motion speed based on the reciprocals of the signal line spectrum frequencies at the three observation moments and the initial side angle;

[0122] Specifically, suppose that at the three observation times t0, t1, and t2, the frequencies of the line spectrum are detected as f1(0), f1(1), and f1(2), respectively, and their reciprocals are The difference between the reciprocals of the line spectrum frequencies detected at the three moments t0, t1, and t2 is obtained from formula (6):

[0123]

[0124]

[0125] Divide (11) by (12) and introduce the frequency change variable:

[0126]

[0127] Then we have:

[0128] cosβ0-cos(α0+β0)=A[cosβ0-cos(α0+α1+β0)] (14)

[0129] According to the trigonometric formula cos(α+β)=cosαcosβ-sinαsinβ, we can deduce from formula (14):

[0130]

[0131] According to formula (8), the inverse of the detection line spectrum frequency at time t0 is:

[0132]

[0133] The inverse of the true line spectrum frequency can be obtained as:

[0134]

[0135] Taking the reciprocal of formula (17-1) gives the true frequency of the line spectrum:

[0136]

[0137] The inverse of the line spectrum frequency detected at time t2 is:

[0138]

[0139] Substitute (17) into (18):

[0140]

[0141] Arranging (19) yields:

[0142]

[0143] By rearranging formula (20), we can get the target motion speed:

[0144]

[0145] (21) In formula, It is the reciprocal of the line spectrum frequencies f1(0) and f1(2) detected at time t0 and t2. α0, α1, and β0 are calculated by equations (1), (2), and (15), respectively.

[0146] S6. Calculate the target distance at the third observation time based on the target speed and initial beam angle and the target distance estimation model established based on the motion triangle; calculate the target heading based on the true bearing line of the sonar observation platform relative to the target and the initial beam angle;

[0147] Specifically, according to the target initial side angle β0 and target speed v T , using geometric principles to obtain the target distance at time t2:

[0148]

[0149] Calculate the true bearing line of the sonar observation platform relative to the target:

[0150]

[0151] According to the initial β0 of the sonar observation platform relative to the moving target, the target's heading is calculated by formula (24):

[0152]

[0153] S7. Repeat the update step size set according to the data refresh rate requirement to update the three observation moments, and execute steps S2 to S6 to form a target distance, target heading and target motion speed estimation sequence, and draw the target dynamic trajectory diagram (polar coordinates or rectangular coordinate system) based on the output estimation sequence.

[0154] Specifically, the target distance R and speed H can be obtained based on the target orientation and line spectrum frequency at the three observation times. T , heading v T Assuming that the target maintains uniform linear motion, we can obtain {R(t i ), H T (t i ), v T (t i )} estimation sequence (where i represents the i-th order of distance and heading speed estimation), thereby obtaining the complete target motion track and speed. There are two implementation methods:

[0155] The first method is to use the time t0 of the first motion parameter estimation as the benchmark and obtain the three observation times of the i-th parameter estimation at a certain observation time interval Δt:

[0156]

[0157] Continuously estimate the target direction and line spectrum frequency observations at t0(i), t1(i), and t2(i);

[0158] Obtain the target direction and line spectrum frequency at the three moments t0(i), t1(i), and t2(i), and follow steps S2 to S6 to obtain {R(t i ), H T (t i ), v T (t i)}Estimated sequence.

[0159] The second method is to keep the observation values ​​of the first two observation moments and the target direction and its line spectrum frequency unchanged, and only change the acquisition time t2 of the third observation value to perform continuous observation estimation, that is:

[0160]

[0161] Obtain the target direction and line spectrum frequency at the three moments t0(i), t1(i), and t2(i), and follow steps S2 to S6 to obtain {R(t i ), H T (t i ), v T (t i )}Estimated sequence.

[0162] Finally, the method of drawing the target motion dynamic trajectory diagram is: starting from the third moment, the target orientation θ(t i ), distance R(t i ), so that the target dynamic trajectory diagram in polar coordinates can be drawn with the stationary observation point O as the pole; it can also be drawn in a rectangular coordinate system through coordinate conversion.

[0163] Theoretically, the accuracy of the above method is related to the length of the observation time and the interval size. The larger the target's azimuth change α0, α1 and radial velocity relative to the receiving point, the higher the estimation accuracy of the target's speed, heading, and distance.

[0164] Simulation Example 1:

[0165] At the initial simulation time t = 0, the target's initial range was 3 km, its initial true bearing was 90 degrees, its heading was 315 degrees, and its velocity was 10.98 m / s. The target signal was generated using a ship-radiated noise signal model (simulating continuous, line, and modulation spectrum characteristics). The target radiated signal source level was 170 dB, and the simulation included three line spectra. This simulation example used a line spectrum with a true frequency of 799 Hz to estimate the target range and motion parameters. The sonar was a uniform 8-element circular array with a radius of 0.5 m and was stationary. The ocean ambient sound source level was 100 dB, the sea depth was 150 m, the seabed was flat, the seawater velocity c = 1500 m / s, and the receiving depth of both the target platform and the sonar was 100 m. The underwater acoustic channel was calculated using the Bellhop model. The calculation times for this example were t0 = 11 seconds, t1 = 41 seconds, and t2 = 86 seconds. The subsequent dynamic trajectory estimation time update method used the second method in S7, with an interval Δt = 10 seconds. The sonar beamforming azimuth process diagram, the tracked target LOFAR spectrum and the comparison results of this example are shown in the figure. Figures 4 to 11 shown.

[0166] Simulation Example 2: The simulation initial time t = 0, the target initial distance is 6km, the initial true azimuth is 240 degrees, the target motion heading is 90°, and the motion speed is 12 meters per second. The ocean environment, sonar parameters, receiving depth and target depth, as well as the target signal simulation parameters are the same as those in Simulation Example 1. This application example uses a line spectrum with a true frequency of 799Hz to estimate the target distance and motion parameters. The calculation time of this example is t0 = 20 seconds, t1 = 65 seconds, and t2 = 105 seconds. The time update method for subsequent dynamic trajectory estimation adopts the second method in S7, with an interval of Δt = 10 seconds. The sonar beamforming azimuth process diagram, the tracked target LOFAR spectrum and the comparison results of this example are shown in the figure. Figures 12 to 19 shown.

[0167] It can be seen from the two simulation examples that the estimated results of target speed, heading and distance are consistent with the theoretical values ​​of the simulation background settings, and the errors are within the allowable range.

[0168] Above-mentioned two kinds of target motion situation examples, the line spectrum Doppler frequency shift variation that target motion causes is very little (variation within 100 seconds only has 1.5Hz, 0.7Hz respectively), present technical invention can all realize target distance, motion speed course and motion trajectory estimation with higher accuracy, and estimation time is very short (two examples are respectively 85 seconds and 105 seconds).And, the precision of each estimation parameter and motion trajectory point are more and more accurate along with the prolongation of observation time.The azimuth rate of change of target motion, Doppler frequency rate of change are larger, and the present invention carries out the effect of target positioning and motion parameter and trajectory estimation better, has good practical application and application value.

[0169] Other beneficial effects:

[0170] 1. The present invention adopts the true azimuth difference (azimuth angle) of target observation as the observation parameter, which can overcome the systematic error of target azimuth observation, thereby improving the estimation accuracy of target distance and motion parameters.

[0171] 2. The present invention proposes an improved Doppler frequency shift model represented by the inverse of the line spectrum frequency, which greatly simplifies the heading and speed estimation model of the moving target. In addition, the difference (variation) of the measured frequency inverse is used as the model input parameter, which can reduce the impact of frequency observation error on the parameter estimation accuracy. As a result, the target distance and motion parameter estimation model under the condition that the Doppler frequency shift can be observed has good stability, simple calculation, and is convenient for engineering application.

[0172] 3. This invention introduces a crucial intermediate variable—the frequency change rate A—which plays a crucial role in estimating the target heading (initial side angle β0) and speed, and can be used to control the accuracy of these parameters. In practical engineering applications, users can set the observation interval based on the magnitude of A, based on the observed Doppler frequency shift, to ensure the stability and reliability of the calculation results.

[0173] 4. The present invention proposes a simple and practical distance calculation analytical model based on geometric principles. By using the target speed and the estimated value of the initial side angle, the target distance at the third observation moment can be quickly and stably solved.

[0174] 5. The present invention proposes a complete method for estimating target motion parameters, position and frequency parameters using only the target orientation and single-line spectrum frequency at three observation moments.

[0175] 6. The present invention proposes a method for dynamically estimating the target motion trajectory (azimuth, distance) and speed and heading based on continuous observation of the target's azimuth and frequency information at three moments. This method can dynamically estimate the target trajectory and motion parameters after the first target parameter estimation at regular time intervals, obtain the azimuth, distance, speed and heading at the continuous observation moments, and then plot a dynamic trajectory diagram of the moving target in polar or rectangular coordinates. This technical invention can achieve a detection effect similar to that of radar (active sonar), and the data refresh rate is not limited by the transmission repetition period, with a data refresh rate of seconds, greatly enriching the passive target indication information and possessing very unique technical advantages.

[0176] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications to the technical solutions described in the above embodiments, or equivalent replacement of some or all of the technical features therein, do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A target range and trajectory estimation method based on stationary passive sonar Doppler, characterized in that: The estimation method includes: S1. Setting simulation motion status; S2. Calculate two angles between the target position and the line connecting the sonar receiving points based on the target true azimuth at the three observation times, where the two angles are the target azimuth changes; S3. Establishing a Doppler frequency shift model for the sonar signal of a stationary platform to obtain the relationship between the signal line spectrum frequency at the three observation times and the target azimuth, target motion speed, and target side angle; S4. Establishing a relationship between the target's subsequent broadside angle, the target's initial broadside angle, and the azimuth change based on a motion triangulation geometric relationship, obtaining an improved Doppler model for estimating motion parameters of a stationary sonar target, and calculating the inverse of the signal line spectrum frequency at the three observation moments; S5. Calculate two differences based on the reciprocals of the line spectrum frequencies at the three observation moments, then calculate the ratio of the two differences to calculate the initial side angle; calculate the target motion speed based on the reciprocals of the signal line spectrum frequencies at the three observation moments and the initial side angle; S6. Calculate the target distance at the third observation moment based on the target movement speed and initial broadside angle and a target distance estimation model established based on the motion triangle; calculate the target heading based on the true bearing line of the sonar observation platform relative to the target and the initial broadside angle; S7. Repeat the updating of the three observation moments according to the update step size set according to the data refresh rate requirement, and execute steps S2 to S6 to form a target distance, target heading and target motion speed estimation sequence, and draw a target dynamic trajectory diagram based on the output estimation sequence.

2. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 1, characterized in that: The setting of the simulation motion situation includes: The sonar receiving array is set to be stationary at point O, and the target T is moving at a speed of v T , initial side angle β0, according to the heading H T Motion; at t0, t1, and t2, the target is located at T0, T1, and T2 respectively, radiating its noise. The stationary sonar detects the target radiation noise signal and measures the true bearing respectively as ψ0, ψ1, and ψ2. The angle between the target heading and the line connecting the receiving array position point O, that is, the side angle of the receiving point relative to the target, is β0, β1, and β2 respectively.

3. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 2, characterized in that: The step S2 includes: α0=|ψ0-ψ1| (1) α1=|ψ2-ψ1| (2).

4. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 3, characterized in that: The step S3 comprises: Set the moving speeds of the moving target platform and the sonar receiving platform to v respectively T and v w , and the target signal has a line spectrum, and the original frequency of the line spectrum is f1, then according to the relative motion Doppler principle, the frequency after Doppler shift is: Assume that at three observation times t i (i=0,1,2.), the line spectrum frequency of the measured signal is: where α i and β i t i The relative side angle between the sonar platform and the target platform at any moment; Because the receiving platform does not move, that is, v w =0, then:

5. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 4, characterized in that: The step S4 comprises: Taking the reciprocal of both sides of formula (5), we get: Introduce the reciprocal variable: i The reciprocal of the target signal line spectrum frequency observed at the moment and the unknown true frequency is: Then formula (6) can be expressed as: Among them, according to the motion triangle geometric relationship diagram, there are: β1＝α0+β0 (9) β2＝α1+β1＝α1+α0+β0 (10) Formula (8) is an improved model of Doppler frequency shift expressed by the inverse of frequency.

6. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 5, characterized in that: Step S5 includes: Assume that at the three observation times t0, t1, and t2, the frequencies of the line spectrum are detected as f1(0), f1(1), and f1(2), respectively, and their reciprocals are The difference between the reciprocals of the line spectrum frequencies detected at the three moments t0, t1, and t2 is obtained from formula (6): Divide (11) by (12) and introduce the frequency change ratio: Then we have: cosβ0-cos(α0+β0)=A[cosβ0-cos(α0+α1+β0)] (14) According to the trigonometric formula cos(α+β)=cosαcosβ-sinαsinβ, we can deduce from formula (14): According to formula (8), the inverse of the detection line spectrum frequency at time t0 is: The inverse of the true line spectrum frequency can be obtained as: Taking the reciprocal of formula (17-1) gives the true frequency of the line spectrum: The inverse of the line spectrum frequency detected at time t2 is: Substitute (17) into (18): Arranging (19) yields: By rearranging formula (20), we can get the target motion speed: Where, It is the reciprocal of the line spectrum frequencies f1(0) and f1(2) detected at time t0 and t2. α0, α1, and β0 are calculated by equations (1), (2), and (15), respectively.

7. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 6, characterized in that: The step S6 comprises: According to the target initial side angle β0 and target speed v T , using geometric principles to obtain the target distance at time t2: Calculate the true bearing line of the sonar observation platform relative to the target: According to the initial side angle β0 of the sonar observation platform relative to the moving target, the target heading is calculated by formula (24):

8. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 7, characterized in that: The forming of a target distance, target heading and target motion speed estimation sequence comprises: Taking the time t0 of the first motion parameter estimation as the benchmark, and with a certain observation time interval Δt, the three observation times of the i-th parameter estimation are obtained: Continuously estimate the target direction and line spectrum frequency observations at t0(i), t1(i), and t2(i); Obtain the target direction and line spectrum frequency at the three moments t0(i), t1(i), and t2(i), and follow steps S2 to S6 to obtain {R(t i ), H T (t i ), v T (t i )}Estimated sequence.

9. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 8, characterized in that: The forming of a target distance, target heading and target motion speed estimation sequence comprises: The first two observation moments and the target azimuth and its line spectrum frequency observation values ​​of the three observation moments remain unchanged, and only the acquisition moment t2 of the third observation value is changed for continuous observation estimation, that is: Obtain the target direction and line spectrum frequency at the three moments t0(i), t1(i), and t2(i), and follow steps S2 to S6 to obtain {R(t i ), H T (t i ), v T (t i )}Estimated sequence.

10. The target distance and trajectory estimation method based on stationary passive sonar Doppler according to claim 8 or 9, characterized in that: Drawing a target dynamic trajectory diagram according to the output estimated sequence includes: Starting from the third moment, the target direction θ(t i ), distance R(t i ), draw the target dynamic trajectory diagram in polar coordinates with the stationary observation point O as the pole, and then convert it to a rectangular coordinate system to draw the target motion trajectory diagram in the rectangular coordinate system.

Images