Target trajectory estimation method, device and equipment based on passive omnidirectional sonar buoy

Abstract

The application relates to a target trajectory estimation method, device and equipment based on a passive omnidirectional sonar buoy, which comprises the following steps: firstly, screening a plurality of sonar buoys closest to a target in a passive omnidirectional sonar buoy array; processing detection signals corresponding to the screened sonar buoys to obtain the closest distance of the target to each screened sonar buoy, the time when the target reaches the closest distance and the motion speed; then taking the coordinates of each screened sonar buoy as a circle center, taking the closest distance as a radius to construct a plurality of circles, taking two circles with close arrival times as a group to calculate the length of a common tangent line, then using a secondary scoring mechanism to obtain the common tangent line with the highest score in each group of circles, taking the corresponding tangent point coordinates as possible trajectory points of the target, finally fitting a plurality of obtained trajectory points to obtain an estimated motion trajectory of the target; and the motion trajectory of the target can be accurately estimated by using the method.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sonobuoy underwater acoustic detection, in particular to a target trajectory estimation method, device and equipment based on a passive omnidirectional sonobuoy. BACKGROUND

[0002] The sonobuoy, also known as a radio sonobuoy, is a main detection device of an aerial anti-submarine aircraft, especially a fixed-wing anti-submarine patrol aircraft. The sonobuoy can be roughly divided into passive sonobuoys and active sonobuoys according to the detection method, wherein the passive omnidirectional sonobuoy, also known as a LOFAR (Low-Frequency Acquisition and Ranging) buoy, is a commonly used buoy that obtains target detection information by passively receiving target radiation noise.

[0003] In the existing positioning method, the array requirement of the CODAR method is very harsh; the time error of the HYFIX method is large, and the method lacks practicability; the directional buoy of the DIFIX method has a very high requirement for the signal-to-noise ratio of a line spectrum, and the direction-finding performance is unreliable. SUMMARY

[0004] Therefore, it is necessary to provide a target trajectory estimation method, device and equipment based on a passive omnidirectional sonobuoy, which can estimate the motion trajectory of a target more accurately.

[0005] A target trajectory estimation method based on a passive omnidirectional sonobuoy, the method comprising:

[0006] obtaining a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passive detection of a target by each sonobuoy in the passive omnidirectional sonobuoy;

[0007] processing each detection signal to obtain a Doppler frequency offset amplitude of the corresponding sonobuoy relative to the target, and screening the sonobuoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonobuoys closest to the target;

[0008] calculating according to the detection signal corresponding to each screened sonobuoy to obtain the closest distance of the target to each screened sonobuoy, the time when the closest distance is reached, and the motion speed of the target;

[0009] taking the coordinates of each screened sonobuoy as a center and the corresponding closest distance as a radius to construct a plurality of circles, and then calculating the common tangent and the corresponding tangent point of two circles with close arrival times.

[0010] According to the common tangent corresponding to the tangent point, the length of each group of common tangents is calculated, and a secondary scoring mechanism is used to score the length of each group of common tangents, and the coordinates corresponding to the tangent point of the common tangent with the highest score in each group of circles are taken as the possible trajectory scatter points of the target;

[0011] The possible trajectory scatter points of the target are fitted to obtain an estimated motion trajectory of the target.

[0012] In one embodiment, the processing of each detection signal to obtain the Doppler frequency offset amplitude corresponding to the sonobuoy relative to the target includes:

[0013] Each detection signal is subjected to a short-time Fourier transform to obtain a corresponding power spectrum, and a part of the power spectrum is obtained by intercepting each power spectrum according to a preset target center frequency;

[0014] After the peak value is calculated by quadratic curve interpolation for the spectral value corresponding to each time in each part of the power spectrum, the frequency point corresponding to the peak value is selected as the target radiation noise frequency measurement value at the corresponding time;

[0015] After all target radiation noise frequency measurement values in each part of the power spectrum are smoothed by a five-point cubic smoothing method, a target radiation noise frequency change graph corresponding to each part of the power spectrum is obtained;

[0016] The difference between the maximum value and the minimum value in each target radiation noise frequency change graph is obtained to obtain the Doppler frequency offset amplitude.

[0017] In one embodiment, when the sonobuoy is screened according to the Doppler frequency offset amplitude, the first few sonobuoys with the largest Doppler frequency offset amplitude are selected as the screened sonobuoys according to a preset number of sonobuoys.

[0018] In one embodiment, the calculation according to the detection signal corresponding to each screened sonobuoy to obtain the closest distance of the target to each screened sonobuoy, the time when the closest distance is reached, and the motion speed of the target includes:

[0019] In the power spectrum corresponding to each screened sonobuoy, any two time points are selected as a first time point and a second time point, and the first frequency and the second frequency corresponding to the two time points are obtained respectively;

[0020] In each corresponding power spectrum, a line spectrum frequency change curve is recorded, an inflection point on the line spectrum frequency change curve is calculated, and a third time and a third frequency corresponding to the inflection point are obtained, the third time and the third frequency being the time and the frequency when the target reaches the closest distance to the sonobuoy respectively;

[0021] According to the first frequency, the second frequency, the third frequency, the first time, the second time and the third time obtained from each corresponding power spectrum diagram, a positioning formula is used to calculate, and the closest distance of the target to each screening sonar buoy and the corresponding target motion speed are obtained respectively.

[0022] In one embodiment, the positioning formula is represented as:

[0023]

[0024]

[0025] wherein, Δt1=T cpa -t1, Δt2=T cpa -t2

[0026] In the above formula, D represents the closest distance of the target to the sonar buoy, v represents the motion speed of the target at the closest distance, t1, t2, T cpa represent the first time, the second time and the third time respectively, F1, F2, f cpa represent the first frequency, the second frequency and the third frequency respectively.

[0027] In one embodiment, the length of each group of common tangent lines is calculated according to the common tangent corresponding to the tangent point, and a two-time scoring mechanism is used to score the length of each group of common tangent lines respectively, which includes:

[0028] The common tangent lines in each group are scored twice in turn. The first time scoring includes: calculating the theoretical length and the actual length of the common tangent line in each group according to the coordinates of the tangent point respectively, and comparing the difference between the two with the preset difference range. If the difference is within the preset difference range, the corresponding common tangent line is scored 1, and if the difference is not within the preset difference range, the corresponding common tangent line is scored 0.

[0029] The second time scoring includes: calculating the distance from the tangent point on the second circle in the group of circles with earlier time to the tangent point on the first circle in the group of circles with later time, and the common tangent line corresponding to the minimum distance is scored 1.

[0030] In one embodiment, the fitting of the possible trajectory scatter points of the target to obtain the estimated motion trajectory of the target includes:

[0031] The polynomial fitting method is used to fit the possible trajectory scatter points of the target to obtain the estimated motion trajectory of the target.

[0032] In one embodiment, the fitting of the possible trajectory scatter points of the target to obtain the estimated motion trajectory of the target includes:

[0033] Filtering the possible trajectory scatter points of the target by using a sliding average method or a Kalman filtering method to obtain more accurate trajectory scatter points;

[0034] Fitting the filtered motion trajectory scatter points by using the polynomial fitting method to obtain the estimated motion trajectory of the target.

[0035] A target trajectory estimation device based on a passive omnidirectional sonobuoy, the device comprising:

[0036] A detection signal acquisition module for acquiring a detection signal dataset, the detection signal dataset comprising a plurality of detection signals obtained by each sonobuoy in the passive omnidirectional sonobuoy passively detecting a target;

[0037] A sonobuoy screening module for processing each detection signal to obtain a Doppler frequency offset amplitude of the corresponding sonobuoy relative to the target, and screening sonobuoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonobuoys closest to the target;

[0038] A closest distance parameter calculation module for calculating according to the corresponding detection signal of each screened sonobuoy to obtain the closest distance of the target to each screened sonobuoy, the time of reaching the closest distance, and the motion speed of the target;

[0039] A circular construction module for taking the coordinates of each screened sonobuoy as the center of a circle and constructing a plurality of circles with the corresponding closest distance as the radius, and then calculating the common tangent and the corresponding tangent point of two circles with close arrival times as a group according to the time of the target reaching the closest distance of each screened sonobuoy;

[0040] A possible trajectory scatter point obtaining module for calculating the length of each group of common tangents according to the corresponding tangent points of the common tangents, and scoring the length of each group of common tangents by using a secondary scoring mechanism, and taking the coordinates of the tangent point of the common tangent with the highest score in each group of circles as the possible trajectory scatter point of the target;

[0041] A motion trajectory estimation fitting module for fitting the possible trajectory scatter points of the target to obtain the estimated motion trajectory of the target.

[0042] A computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0043] Acquiring a detection signal dataset, the detection signal dataset comprising a plurality of detection signals obtained by each sonobuoy in the passive omnidirectional sonobuoy passively detecting a target;

[0044] processing each of the detection signals to obtain a Doppler frequency shift amplitude of the corresponding sonobuoy relative to the target, and screening the sonobuoys according to the Doppler frequency shift amplitudes to obtain a plurality of screened sonobuoys closest to the target;

[0045] calculating according to the detection signals corresponding to each of the screened sonobuoys to obtain a closest distance of the target to each of the screened sonobuoys in travel, a time of arrival at the closest distance, and a movement speed of the target;

[0046] taking the coordinates of each of the screened sonobuoys as a center and the corresponding closest distance as a radius to construct a plurality of circles, and then calculating a common tangent and a corresponding tangent point of two circles with proximal arrival times as a group according to the times of arrival of the target at the closest distances of each of the screened sonobuoys;

[0047] calculating the lengths of the common tangents of each group according to the tangent points corresponding to the common tangents, and scoring the lengths of the common tangents of each group respectively by using a secondary scoring mechanism, and taking the coordinates of the tangent points of the common tangent with the highest score in each group of circles as possible trajectory scatter points of the target;

[0048] fitting the possible trajectory scatter points of the target to obtain an estimated movement trajectory of the target.

[0049] A computer readable storage medium having stored thereon a computer program, the computer program being executed by a processor to implement the following steps:

[0050] obtaining a detection signal dataset, the detection signal dataset including a plurality of detection signals obtained by each sonobuoy of a plurality of passive omnidirectional sonobuoys passively detecting a target;

[0051] processing each of the detection signals to obtain a Doppler frequency shift amplitude of the corresponding sonobuoy relative to the target, and screening the sonobuoys according to the Doppler frequency shift amplitudes to obtain a plurality of screened sonobuoys closest to the target;

[0052] calculating according to the detection signals corresponding to each of the screened sonobuoys to obtain a closest distance of the target to each of the screened sonobuoys in travel, a time of arrival at the closest distance, and a movement speed of the target;

[0053] taking the coordinates of each of the screened sonobuoys as a center and the corresponding closest distance as a radius to construct a plurality of circles, and then calculating a common tangent and a corresponding tangent point of two circles with proximal arrival times as a group according to the times of arrival of the target at the closest distances of each of the screened sonobuoys;

[0054] The lengths of the common tangent lines of each group are calculated according to the common tangent point, and a secondary scoring mechanism is used to score the lengths of the common tangent lines of each group, and the coordinates of the tangent points corresponding to the highest score in each group of circles are taken as the possible trajectory points of the target.

[0055] The estimated motion trajectory of the target is obtained by fitting the possible trajectory points of the target.

[0056] The above-mentioned target trajectory estimation method, device and equipment based on passive omnidirectional sonobuoy, first screen the multiple sonobuoys closest to the target in the passive omnidirectional sonobuoy array, process the detection signals corresponding to the screened sonobuoys to obtain the closest distance of the target to each screened sonobuoy, the time when the target reaches the closest distance, and the motion speed, then take the coordinates of each screened sonobuoy as the center of a circle, and the closest distance as the radius to construct multiple circles, and calculate the length of the common tangent line of two circles with close arrival times as a group, then use a secondary scoring mechanism to obtain the common tangent line with the highest score in each group of circles, and take the coordinates of the corresponding tangent point as the possible trajectory point of the target, finally fit the obtained multiple trajectory points to obtain the estimated motion trajectory of the target. The motion trajectory of the target can be accurately estimated using the method. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 A flowchart of the target trajectory estimation method based on passive omnidirectional sonobuoy in one embodiment is shown.

[0058] Figure 2 A schematic diagram of the position of the ship and the buoy in one embodiment is shown.

[0059] Figure 3 A flowchart of the secondary scoring mechanism method in one embodiment is shown.

[0060] Figure 4 A structure block diagram of the target trajectory estimation device based on passive omnidirectional sonobuoy in one embodiment is shown.

[0061] Figure 5 An internal structure diagram of the computer device in one embodiment is shown. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0063] As shown in Figure 1 , a target trajectory estimation method based on passive omnidirectional sonobuoy is provided, comprising the following steps:

[0064] Step S100, obtaining a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by each passive omnidirectional sonobuoy in the passive omnidirectional sonobuoy array passively detecting the target;

[0065] Step S110, processing each detection signal to obtain a Doppler frequency offset amplitude of the corresponding sonobuoy relative to the target, and screening the sonobuoys according to the Doppler frequency offset amplitudes to obtain a plurality of screened sonobuoys closest to the target;

[0066] Step S120, calculating according to the detection signal corresponding to each screened sonobuoy to obtain a closest distance of the target to each screened sonobuoy when the target is moving, a time when the target reaches the closest distance, and a moving speed of the target;

[0067] Step S130, taking the coordinates of each screened sonobuoy as the center of a circle and the corresponding closest distance as the radius to construct a plurality of circles, and then calculating the common tangent and the corresponding tangent point of two circles adjacent in time when the target reaches the closest distance to each screened sonobuoy;

[0068] Step S140, calculating the length of the common tangent of each group of common tangents according to the corresponding tangent point of the common tangent, and scoring the length of the common tangent of each group of common tangents respectively by using a secondary scoring mechanism, and taking the coordinates of the tangent point corresponding to the common tangent with the highest score in each group of circles as the possible trajectory points of the target;

[0069] Step S150, fitting the possible trajectory points of the target to obtain an estimated moving trajectory of the target.

[0070] In the embodiment, first, the sonobuoys closest to the target in the passive omnidirectional sonobuoy array are screened, the detection data obtained by the screened sonobuoys are processed to obtain the closest distance of the moving target to the sonobuoys and the corresponding time. Then, the coordinates of each screened sonobuoy are taken as the center of a circle and the closest distance is taken as the radius to construct a circle, and two adjacent circles are taken as a group to determine the common tangent and the length thereof. Here, the common tangent segments of each group of circles are scored by using a secondary scoring mechanism, and the coordinates of the tangent point corresponding to the common tangent with the highest score in each group are taken as the possible trajectory points of the target. Then, the plurality of possible trajectory points are fitted to obtain the accurate moving trajectory of the target.

[0071] In step S100, each sonobuoy in the passive omnidirectional sonobuoy array is a passive omnidirectional sonobuoy, and the target can be a ship sailing on the water surface or a submarine sailing on the water bottom. In this paper, the method is described by taking a ship as an example.

[0072] In step S110, when the ship (target) passes by the passive omnidirectional sonar buoy array, not all the detection data obtained by the passive omnidirectional sonar buoy array is of reference value, and all the detection data does not need to be processed. Therefore, in order to improve efficiency and accuracy, only the detection signals of the sonar buoys closest to the target need to be processed. Therefore, in the method, the Doppler frequency shift amplitude is used to screen the sonar buoys, and the detection data with a larger shift amplitude is selected for subsequent processing.

[0073] In the embodiment, obtaining the Doppler frequency shift amplitude of the corresponding sonar buoy relative to the target by processing each detection signal includes: performing short-time Fourier transform on each detection signal to obtain a corresponding power spectrum diagram, and cutting each power spectrum diagram according to a preset target center frequency to obtain a partial power spectrum diagram. Then, after performing quadratic curve interpolation on the spectral value corresponding to each time in each partial power spectrum diagram to obtain a peak value, the frequency point corresponding to the peak value is selected as the target radiation noise frequency measurement value at the corresponding time. Then, after performing five-point cubic smoothing on all the target radiation noise frequency measurement values in each partial power spectrum diagram, a target radiation noise frequency change diagram corresponding to each partial power spectrum diagram is obtained. Finally, the difference between the maximum value and the minimum value in each target radiation noise frequency change diagram is obtained to obtain the Doppler frequency shift amplitude.

[0074] Specifically, first, the center frequency of the ship is selected. Second, partial power spectrum diagrams within a certain range to the left and right of the center frequency are selected. Then, since the detection data is discrete, the sample point obtained by finding the peak value of the detection signal is often not a local maximum value, but between two adjacent sample points. Therefore, interpolation is needed to obtain the true local maximum value. In the method, a quadratic curve (parabola) is used for interpolation. After performing quadratic curve interpolation on the LOFAR (power spectrum) spectral value at each time to find the peak value, the frequency point with the largest amplitude is selected as the ship radiation noise frequency measurement value at this time. Finally, all the ship radiation noise frequency measurement values are smoothed by using a five-point cubic smoothing method to obtain a predicted ship radiation noise frequency change diagram. Since the extracted frequency change curve is not smooth enough, the five-point cubic smoothing method is used for smoothing. The five-point cubic smoothing method is a processing method for smoothing discrete data by using the least square method. The difference between the maximum value and the minimum value of the smoothed frequency change diagram is obtained to obtain the Doppler frequency shift amplitude.

[0075] Specifically, let x(n), n = 1, 2,..., N be a sequence, and y(n) be the output of x(n) after five-point cubic smoothing. The calculation formula of the five-point cubic smoothing method is as follows:

[0076]

[0077] In the embodiment, when the sonobuoy is screened according to the Doppler frequency shift amplitude, the first several sonobuoys with the largest Doppler frequency shift amplitude are selected as the screened sonobuoys according to the preset number of sonobuoys.

[0078] Then, in step S120, a new positioning method is provided, including: selecting any two time points in each power spectrum corresponding to the screened sonobuoy as a first time point and a second time point respectively, and correspondingly obtaining a first frequency and a second frequency corresponding to the two time points respectively, while recording a line spectrum frequency change curve in each corresponding power spectrum, finding an inflection point on the line spectrum frequency change curve, and obtaining a third time and a third frequency corresponding to the inflection point, the third time and the third frequency being a time and a frequency at which the target reaches the closest distance to the sonobuoy respectively. According to the first frequency, the second frequency, the third frequency, the first time, the second time and the third time obtained from each corresponding power spectrum, a positioning formula is used for calculation to obtain the closest distance of the target to each screened sonobuoy and the corresponding target motion speed respectively.

[0079] Further, the positioning formula is expressed as:

[0080]

[0081]

[0082] Wherein, Δt1=T cpa -t1, Δt2=T cpa -t2

[0083] In formulas (2) and (3), D represents the closest distance of the target to the sonobuoy, v represents the motion speed of the target at the closest distance, t1, t2, T cpa represent the first time, the second time and the third time respectively, F1, F2, f cpa represent the first frequency, the second frequency and the third frequency respectively.

[0084] Specifically, since there is a narrowband line spectrum component with a higher frequency in the LOFAR spectrum of the ship radiated noise, the ship first approaches the sonobuoy and then moves away, according to the Doppler effect, the LOFAR spectrum line of the sonobuoy signal will move from high to low, and the closest point of the sonobuoy to the target is the CPA (closest point of approach) point, and the position map of the ship and the sonobuoy is as shown in Figure 2 .

[0085] According to the Doppler shift formula, the line spectrum frequency detected by the sonobuoy is:

[0086]

[0087] In formula (4), f represents the measured target frequency, f represents the center frequency of the ship, v represents the running speed of the ship, represents the included angle of the ship heading to the buoy connecting line, and c represents the sound speed in water.

[0088] In the LOFAR spectrum, the frequencies of two time points t1 and t2 are F1 and F2 respectively, and formula (4) can be obtained:

[0089]

[0090]

[0091] When the ship moves from close to the buoy to far away from the buoy, the LOFAR line spectrum frequency always decreases (from greater than the ship target center frequency to less than the ship target center frequency), and the change of the LOFAR line spectrum frequency is recorded, and the inflection point of the line spectrum curve is obtained, then the frequency f of the ship target reaching the CPA point can be obtained cpa and time T cpa .

[0092] Let: Δt1 = T cpa -t1, Δt2 = T cpa -t2.

[0093] From formula (4), we can know that:

[0094] f cpa = f0 (7)

[0095]

[0096]

[0097] Square both sides of formula (8) and formula (9) and simplify, and let Then formula (2) and formula (3) can be obtained. In these two equations, t1, t2, y1, y2 are known, and then v and D can be obtained.

[0098] The new target positioning method based on Doppler analysis proposed in this paper uses time information, and t1, t2, F1, F2, T cpa , f cpa are relatively easy to obtain, and do not need two observation points to be symmetrical about the CPA point.

[0099] Next, in steps S130 and S140, more accurate ship trajectory points are obtained by calculating and scoring the length of the tangent.

[0100] Specifically, taking each buoy position as the center of a circle and the closest point distance D between the buoy and the ship target as the radius, the time at which the ship reaches the closest distance of each screening sonar buoy is calculated, and two circles with similar arrival times are grouped to calculate their common tangent and corresponding tangent points.

[0101] Let the equations of two adjacent circles be:

[0102] C1:(x-x1) 2 +(y-y1) 2 =r1 2 (10)

[0103] C2:

[0104] In formulas (10) and (11), (x1, y1) and (x2, y2) are the centers of circles C1 and C2, respectively, and r1 and r2 are the radii of circles C1 and C2, respectively. Let:

[0105] Δ + =(x1-x2) 2 +(y1-y2) 2 -(r1+r2) 2 (12)

[0106] Δ - =(x1-x2) 2 +(y1-y2) 2 -(r1-r2) 2 (13)

[0107]

[0108]

[0109] q=x1y2-x2y1 (16)

[0110] Then the common tangent equation of the two circles is as follows:

[0111]

[0112]

[0113]

[0114]

[0115] According to the position relationship of the two adjacent circles, each group of circles can have at most four common tangents. In this method, a two-time scoring mechanism is used to screen one common tangent in each group of circles, and the tangent point coordinates are taken as the ship's trajectory points.

[0116] Specifically, the first scoring includes: calculating the theoretical length and the actual length of the common tangent respectively according to the tangent point coordinates in each group, and comparing the difference between the two with the preset difference range, if the difference is within the preset difference range, then adding 1 point to the corresponding common tangent, if the difference is not within the preset difference range, then adding 0 point to the corresponding common tangent.

[0117] The second scoring includes: calculating the distance from the tangent point on the second circle in the time-earlier group to the tangent point on the first circle in the time-later group, and adding 1 point to the common tangent corresponding to the minimum distance.

[0118] Specifically, the twice scoring mechanism processes according to the flow as shown in Figure 3 The first scoring mechanism: the tangent length is calculated by using the tangent point coordinates on each group of circles, and then the tangent point speed (calculated according to uniform acceleration or uniform deceleration) and the time difference are calculated by using a new method based on Doppler analysis, thereby the theoretical tangent length can be obtained, and then the two are compared, a difference threshold is set, and a voting mechanism is used, if within the difference range, 1 point is given to the corresponding common tangent, if not within the range, 0 point is given, then each common tangent is scored, and when there are multiple circles tangent, multiple common tangents, all common tangents are scored according to this.

[0119] The second scoring mechanism: the distance from the tangent point on the second circle in the time-earlier group to the tangent point on the first circle in the time-later group is calculated, and 1 point is added to the tangent corresponding to the minimum distance. According to the twice scoring mechanism, the tangent with the highest score in each group of circles is selected, and the tangent point on the tangent with the highest score is taken as the predicted ship running track point.

[0120] After obtaining the possible track scatter points of the ship, then in step S150, after error analysis on all the possible track scatter points of the target obtained, the track is fitted to obtain the track equation.

[0121] In this embodiment, after the located scatter points are removed from the singular values, the polynomial fitting method or the sliding average method or the Kalman filtering method is used, and the positioning point error confidence prediction boundary under the preset confidence probability is also calculated, and the confidence range is calculated using the following formula:

[0122]

[0123] In formula (21), b is the coefficient generated by fitting, t depends on the confidence probability and uses the inverse operation of the t cumulative distribution function, S is the vector of the diagonal elements in the estimated covariance matrix of the coefficient estimation, (X T X) -1 s 2 In linear fitting, X is the design matrix, and for nonlinear fitting, X is the Jacobian of the fitting value with respect to the coefficient, XT is the transpose of X, s 2 is the mean square error.

[0124] In the method, one of a polynomial fitting method, a moving average method or a Kalman filtering method is used for error analysis, or the three methods are used simultaneously for error analysis.

[0125] Specifically, when the polynomial fitting method is used for error analysis on the scattered points, the coefficients of an n-th order polynomial p(x) are returned, and the order is the best fitting (in the least square method) of the data in y. The coefficients in p are arranged in descending powers, and the length of p is n+1, that is:

[0126] p(x) = p1x n + p2x n-1 + … + p n x + p n+1 (22)

[0127] Specifically, when the moving average method is used for error analysis, the moving average method is a signal smoothing method in the time domain. The algorithm idea is to take the arithmetic average of the sampling points near the point as the smoothed value of the point. Generally, the window is a symmetric window to prevent phase deviation. The window is generally an odd number, and the 3-point average (window length is 3) formula is taken as an example. The original data is x, and the smoothed data is y:

[0128]

[0129] The moving average function is used for data smoothing, and the average value in each window is obtained by moving the fixed length window.

[0130] Specifically, when the Kalman filtering method is used for error analysis, Kalman filtering mainly optimally estimates the state of the system through the "prediction" and "update" processes. The core process formula is as follows:

[0131] The state prediction equation is:

[0132]

[0133] In formula (24), F is the state transition matrix, is the optimal estimation value of the state at the last time, B is the control matrix, and u t-1 is the system control amount at the last time. The prediction error covariance matrix is:

[0134] P t - = FP t-1 F T+ Q (25)

[0135] In formula (25), P t-1 is the estimation error covariance matrix of the last time, and Q is the state noise covariance matrix. The Kalman gain matrix K under the optimal estimation condition is:

[0136] K t = P t - H T (HP t - H T + R) -1 (26)

[0137] In formula (26) above, H is the control matrix of the observation matrix, and R is the observation covariance matrix. The state update equation is:

[0138]

[0139] In formula (27) above, z t is the observation matrix.

[0140] The estimation error covariance matrix is:

[0141] p t = (1-K t H)P t - (28)

[0142] In fact, if the polynomial fitting method is used to fit the motion trajectory scatter points, the motion trajectory equation of the target and the confidence prediction boundary can be directly obtained. When the other two methods are used, the moving average method or Kalman filtering method is used to filter the possible trajectory scatter points of the target to obtain more accurate trajectory scatter points, and then the polynomial fitting method is used to fit the filtered motion trajectory scatter points to obtain the estimated motion trajectory of the target.

[0143] In the target trajectory estimation method based on the passive omnidirectional sonobuoy above, in the method, the Doppler frequency offset is searched in a wide frequency spectrum interval of the LOFAR spectrum diagram, the peak value method of quadratic curve interpolation is used to extract the frequency change curve, the five-point cubic smoothing method is used to smooth the frequency change curve, the Doppler frequency offset of each sonobuoy is automatically calculated, the sonobuoy participating in the Doppler-CPA positioning is automatically given by comparing the offset proportions of the sonobuoy, and the possible positioning point of the target is obtained by using a twice-scoring mechanism. The first scoring mechanism: the theoretical tangent length and the actual tangent length are used to score by the voting mechanism. The second scoring mechanism: the distance between the tangent points on the adjacent two groups of circles is calculated, and the tangent line corresponding to the minimum distance is added one point. According to the twice-scoring mechanism, the tangent line with the highest score in each group of circles is selected, and the tangent point on the tangent line with the highest score is the possible positioning point of the target. Finally, the motion trajectory of the target is estimated by using three error estimation models of the polynomial fitting method, the moving average method and the Kalman filtering method. The target track can be more accurately positioned by using the method.

[0144] It should be understood that, although Figure 1 the steps in the flowchart of the method are shown in sequence according to the arrows, these steps are not necessarily executed in sequence according to the arrows. Unless otherwise explicitly stated herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, Figure 1 at least part of the steps in the method can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of the sub-steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or sub-steps or stages of other steps.

[0145] In one embodiment, as shown in Figure 4 , a target trajectory estimation device based on passive omnidirectional sonobuoy is provided, comprising: a detection signal acquisition module 200, a sonobuoy screening module 210, a nearest distance parameter calculation module 220, a circle construction module 230, a possible trajectory scatter point obtaining module 240 and an estimation motion estimation fitting module 250, wherein:

[0146] The detection signal acquisition module 200 is configured to acquire a detection signal data set, wherein the detection signal data set includes a plurality of detection signals obtained by passive detection of a target by each sonobuoy in the passive omnidirectional sonobuoy;

[0147] The sonobuoy screening module 210 is configured to process each of the detection signals to obtain a Doppler frequency offset amplitude of a corresponding sonobuoy relative to the target, and screen the sonobuoy according to the Doppler frequency offset amplitude to obtain a plurality of screened sonobuoys closest to the target.

[0148] The closest distance parameter calculation module 220 is configured to calculate according to the detection signal corresponding to each of the screened sonobuoys to obtain a closest distance of the target to each of the screened sonobuoys in travel, a time of arrival at the closest distance, and a movement speed of the target.

[0149] The circular construction module 230 is configured to take the coordinates of each of the screened sonobuoys as a center of a circle, construct a plurality of circles with a corresponding closest distance as a radius, and calculate a common tangent and a corresponding tangent point of two circles with a time of arrival close to each other according to the time of arrival of the target at the closest distance of each of the screened sonobuoys.

[0150] The possible trajectory scatter point obtaining module 240 is configured to calculate a length of each group of common tangents according to the tangent point corresponding to the common tangent, and score the length of each group of common tangents respectively by using a secondary scoring mechanism, and take the coordinates of the tangent point of the common tangent with the highest score in each group of circles as possible trajectory scatter points of the target.

[0151] The motion trajectory estimation fitting module 250 is configured to fit the possible trajectory scatter points of the target to obtain an estimated motion trajectory of the target.

[0152] The specific limitations of the target trajectory estimation device based on the passive omnidirectional sonobuoy can refer to the limitations of the target trajectory estimation method based on the passive omnidirectional sonobuoy in the foregoing, which will not be described here. Each module in the target trajectory estimation device based on the passive omnidirectional sonobuoy can be realized by software, hardware, and a combination thereof in whole or in part. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in a computer device in software form, so as to be called and executed by a processor to perform the operations corresponding to each module.

[0153] In one embodiment, a computer device is provided, which can be a terminal, and an internal structure diagram of the computer device can be as shown in Figure 5As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The network interface of the computer device is used to communicate with the external terminal through the network connection. The computer program is executed by the processor to implement a target trajectory estimation method based on a passive omnidirectional sonobuoy. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0154] Those skilled in the art can understand that, Figure 5 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0155] In one embodiment, a computer device is provided, comprising a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the following steps:

[0156] Obtaining a detection signal data set, the detection signal data set including a plurality of detection signals obtained by each sonobuoy in the passive omnidirectional sonobuoy passively detecting a target;

[0157] Processing each of the detection signals to obtain a Doppler frequency offset amplitude of the corresponding sonobuoy relative to the target, and screening the sonobuoy according to the Doppler frequency offset amplitude to obtain a plurality of screened sonobuoys closest to the target;

[0158] According to the corresponding detection signal of each of the screened sonobuoys, the closest distance of the target to each of the screened sonobuoys in the travel, the time of reaching the closest distance and the motion speed of the target are obtained;

[0159] Taking the coordinates of each of the screened sonobuoys as the center and the corresponding closest distance as the radius, a plurality of circles are constructed, and according to the time of the target reaching the closest distance of each of the screened sonobuoys, two circles with close arrival times are calculated as a group to obtain their common tangent and the corresponding tangent point;

[0160] According to the common tangent corresponding to the tangent point, the length of each group of common tangents is calculated, and a secondary scoring mechanism is used to score the length of each group of common tangents, and the coordinates corresponding to the tangent points of the common tangent with the highest score in each group of circles are taken as the possible trajectory scatter points of the target;

[0161] The possible trajectory scatter points of the target are fitted to obtain the estimated motion trajectory of the target.

[0162] In one embodiment, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the following steps:

[0163] A detection signal data set is obtained, which includes a plurality of detection signals obtained by each sonobuoy in a passive omnidirectional sonobuoy buoy against the target;

[0164] The Doppler frequency offset amplitude of the corresponding sonobuoy relative to the target is obtained by processing each detection signal, and the sonobuoy is screened according to the Doppler frequency offset amplitude to obtain a plurality of screened sonobuoys closest to the target;

[0165] According to the corresponding detection signal of each screened sonobuoy, the closest distance of the target to each screened sonobuoy, the time when the closest distance is reached, and the motion speed of the target are obtained;

[0166] The coordinates of each screened sonobuoy are taken as the center of a circle, and the corresponding closest distance is taken as the radius to construct a plurality of circles, and according to the time when the target reaches the closest distance of each screened sonobuoy, two circles with close arrival times are taken as a group to calculate their common tangents and corresponding tangent points;

[0167] According to the common tangent corresponding to the tangent point, the length of each group of common tangents is calculated, and a secondary scoring mechanism is used to score the length of each group of common tangents, and the coordinates corresponding to the tangent points of the common tangent with the highest score in each group of circles are taken as the possible trajectory scatter points of the target;

[0168] The possible trajectory scatter points of the target are fitted to obtain the estimated motion trajectory of the target.

[0169] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, databases, or other media in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0170] The technical features of the above embodiments can be combined in any way. In order to make the description simple, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present application.

[0171] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of the patent of the present application should be subject to the appended claims.

Claims

1. A target trajectory estimation method based on passive omnidirectional sonar buoys, characterized in that, The method includes: Acquire a detection signal dataset, which includes multiple detection signals obtained by each sonar buoy in a passive omnidirectional sonar buoy passively detecting the target; The detection signals are processed to obtain the Doppler frequency offset amplitude of the corresponding sonar buoy relative to the target, and the sonar buoys are screened according to the Doppler frequency offset amplitude to obtain the multiple screened sonar buoys closest to the target; The closest distance of the target to each of the selected sonar buoys, the time it takes to reach the closest distance, and the target's speed are calculated based on the detection signals corresponding to each of the selected sonar buoys during the journey. Using the coordinates of each of the selected sonar buoys as the center, construct multiple circles with the corresponding nearest distance as the radius. Then, based on the time it takes for the target to reach the nearest distance from each of the selected sonar buoys, group the two circles with adjacent arrival times together and calculate their common tangent and corresponding tangent point. The length of each group of common tangents is calculated based on the corresponding tangent points, and a secondary scoring mechanism is used to score the length of each group of common tangents. The coordinates of the tangent point corresponding to the highest score in each group of circles are used as the possible trajectory scatter points of the target. The calculation of the length of each group of common tangents based on the corresponding tangent points and the secondary scoring mechanism for scoring the length of each group of common tangents includes: scoring the common tangents in each group twice. The first scoring includes: calculating the theoretical length and actual length of the common tangent in each group based on the coordinates of the tangent points, and comparing the difference between the two with a preset difference range. If the difference is within the preset difference range, 1 point is added to the corresponding common tangent; if the difference is not within the preset difference range, 0 points are added to the corresponding common tangent. The second scoring includes: calculating the distance from the tangent point on the second circle in the earlier group of circles to the tangent point on the first circle in the later group of circles, and adding 1 point to the common tangent corresponding to the smallest distance. The possible trajectory points of the target are fitted to obtain the estimated motion trajectory of the target.

2. The target trajectory estimation method according to claim 1, characterized in that, The process of processing each of the detection signals to obtain the corresponding Doppler frequency shift amplitude of the sonar buoy relative to the target includes: The short-time Fourier transform of each of the detection signals is performed to obtain the corresponding power spectrum, and a partial power spectrum is obtained by truncating each of the power spectrum according to the preset target center frequency. After obtaining the peak value by quadratic curve interpolation of the spectral value at each time point in each of the aforementioned partial power spectrum diagrams, the frequency point corresponding to the peak value is selected as the target radiated noise frequency measurement value at the corresponding time point. After smoothing all the target radiated noise frequency measurements in each of the aforementioned partial power spectrum diagrams using a five-point cubic smoothing method, the target radiated noise frequency variation diagrams corresponding to each of the aforementioned partial power spectrum diagrams are obtained. The Doppler frequency shift amplitude is obtained by the difference between the maximum and minimum values ​​in the frequency variation graphs of the target radiated noise.

3. The target trajectory estimation method according to claim 2, characterized in that, When screening sonar buoys based on the Doppler frequency offset amplitude, the first few sonar buoys with the largest Doppler frequency offset amplitude are selected as the screening sonar buoys according to the preset number of sonar buoys.

4. The target trajectory estimation method according to claim 3, characterized in that, The calculation based on the detection signals corresponding to each of the selected sonar buoys to obtain the closest distance of the target to each selected sonar buoy during its movement, the time corresponding to reaching the closest distance, and the target's speed includes: In the power spectrum diagrams of each of the aforementioned sonar buoys, any two moments are selected as the first moment and the second moment, and the first frequency and the second frequency corresponding to these two moments are obtained accordingly. Record the line spectrum frequency change curve in each corresponding power spectrum diagram, find the inflection point on the line spectrum frequency change curve, and obtain the third time and third frequency corresponding to the inflection point. The third time and third frequency are the time and frequency at which the target reaches the closest distance to the sonar buoy, respectively. Based on the first frequency, second frequency, third frequency, first time, second time, and third time obtained from the corresponding power spectrum diagrams, the positioning formula is used to calculate the closest distance between the target and each selected sonar buoy and the corresponding target movement speed.

5. The target trajectory estimation method according to claim 4, characterized in that, The positioning formula is expressed as follows: in, , , In the above formula, This indicates the closest distance between the target and the sonar buoy. This indicates the speed of the target at its closest distance. , , These represent the first time, the second time, and the third time, respectively. , , These represent the first frequency, the second frequency, and the third frequency, respectively.

6. The target trajectory estimation method according to claim 5, characterized in that, The process of fitting the possible trajectory scatter points of the target to obtain the estimated motion trajectory of the target includes: The possible trajectory points of the target are fitted using a polynomial fitting method to obtain the estimated motion trajectory of the target.

7. The target trajectory estimation method according to claim 5, characterized in that, The process of fitting the possible trajectory scatter points of the target to obtain the estimated motion trajectory of the target includes: The possible trajectory points of the target are filtered by the moving average method or the Kalman filter method to obtain more accurate trajectory points. The filtered motion trajectory scatter points are fitted using a polynomial fitting method to obtain the estimated motion trajectory of the target.

8. A target trajectory estimation device based on a passive omnidirectional sonar buoy, characterized in that, The device includes: The detection signal acquisition module is used to acquire a detection signal dataset, which includes multiple detection signals obtained by each sonar buoy in the passive omnidirectional sonar buoy passively detecting the target. The sonar buoy screening module is used to process each of the detection signals to obtain the Doppler frequency offset amplitude of the corresponding sonar buoy relative to the target, and to screen the sonar buoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys that are closest to the target. The closest distance parameter calculation module is used to calculate the closest distance of the target to each of the selected sonar buoys, the time corresponding to reaching the closest distance, and the speed of the target based on the detection signals corresponding to each of the selected sonar buoys during the journey. The circular construction module is used to construct multiple circles with the coordinates of each of the selected sonar buoys as the center and the corresponding nearest distance as the radius. Then, based on the time it takes for the target to reach the nearest distance from each of the selected sonar buoys, the common tangent and the corresponding tangent point are calculated for two circles with adjacent arrival times. The possible trajectory scatter point acquisition module is used to calculate the length of each group of common tangents based on the corresponding tangent points, and to score the length of each group of common tangents using a secondary scoring mechanism. The coordinates of the tangent point corresponding to the highest score in each group of circles are taken as the possible trajectory scatter points of the target. The calculation of the length of each group of common tangents based on the corresponding tangent points and the scoring of the length of each group of common tangents using a secondary scoring mechanism include: scoring the common tangents in each group twice. The first scoring includes: calculating the theoretical length and actual length of the common tangent in each group based on the coordinates of the tangent points, and comparing the difference between the two with a preset difference range. If the difference is within the preset difference range, 1 point is added to the corresponding common tangent; if the difference is not within the preset difference range, 0 points are added to the corresponding common tangent. The second scoring includes: calculating the distance from the tangent point on the second circle in the earlier group of circles to the tangent point on the first circle in the later group of circles, and adding 1 point to the common tangent corresponding to the smallest distance. The motion trajectory estimation and fitting module is used to fit the possible trajectory scatter points of the target to obtain the estimated motion trajectory of the target.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-7.

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