CN116643281A - Target track estimation method, device and equipment based on passive omnidirectional sonar buoy - Google Patents
Target track estimation method, device and equipment based on passive omnidirectional sonar buoy Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The application relates to a target track estimation method, a device and equipment based on passive omni-directional sonar buoys, which are characterized in that a plurality of sonar buoys closest to a target in a passive omni-directional sonar buoys are screened, detection signals corresponding to the screened sonar buoys are processed to obtain the closest distance between the target and each screened sonar buoy and the time and the movement speed corresponding to the closest distance between the target and each screened sonar buoy, then a plurality of circles are constructed by taking the coordinates of each screened sonar buoy as the circle center and the closest distance as the radius, the lengths of common tangent lines of two circles with adjacent arrival times are calculated as a group, then a secondary scoring mechanism is utilized to obtain the common tangent line with the highest score in each group of circles, the coordinates of the corresponding tangent points are taken as possible track points of the target, and finally the obtained plurality of track points are fitted to obtain the estimated movement track of the target.
Description
Technical Field
The application relates to the technical field of sonar buoy underwater sound detection, in particular to a target track estimation method, device and equipment based on a passive omnidirectional sonar buoy.
Background
The sonar buoy is also called as a wireless electroacoustic sonar buoy and is a main detection device of an aviation anti-diving aircraft, in particular to a fixed wing anti-diving patrol machine. Sonar buoys can be broadly divided into passive sonar buoys, also known as LOFAR (Low-Frequency Acquisition and Ranging), and active sonar buoys, according to detection methods, wherein the passive omnidirectional sonar buoys are a common buoy that passively receives target radiation noise to obtain target detection information.
In the existing positioning method, the array requirement of the CODAR method is very strict; the HYFIX method has large time error and lacks practicality; the DIFIX method directional buoy has high requirements on the signal-to-noise ratio of a line spectrum, and the direction finding performance is unreliable.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method, an apparatus and a device for estimating a target trajectory based on a passive omnidirectional sonar buoy, which can more accurately estimate a motion trajectory of a target.
A target trajectory estimation method based on passive omni-directional sonar buoys, the method comprising:
acquiring a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in passive omnidirectional sonar buoys;
Processing each detection signal to obtain Doppler frequency offset amplitude of a corresponding sonar buoy relative to the target, and screening the sonar buoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys nearest to the target;
calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance between the target and each screening sonar buoy in the advancing process, the corresponding time when the nearest distance is reached and the movement speed of the target;
taking the coordinates of each screening sonar buoy as a circle center, constructing a plurality of circles by taking the corresponding nearest distance as a radius, and calculating a common tangent line and a corresponding tangent point of each circle with two circles with adjacent arrival time as a group according to the time of the target reaching the nearest distance from each screening sonar buoy;
calculating the length of each group of common tangent lines according to the corresponding tangent points of the common tangent lines, respectively scoring the length of each group of common tangent lines by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent line with the highest score in each group of circles as possible track scattered points of the target;
and fitting possible track scattered points of the target to obtain an estimated motion track of the target.
In one embodiment, the processing the detection signals to obtain the doppler frequency shift amplitude of the corresponding sonar buoy relative to the target includes:
respectively carrying out short-time Fourier transform on each detection signal to obtain a corresponding power spectrogram, and intercepting each power spectrogram according to a preset target center frequency to obtain a part of power spectrogram;
performing quadratic curve interpolation on the spectrum value corresponding to each moment in each partial power spectrogram to obtain a peak value, and selecting a frequency point corresponding to the peak value as a target radiation noise frequency measurement value at the corresponding moment;
smoothing all the target radiation noise frequency measured values in each partial power spectrogram by adopting a five-point three-time smoothing method to obtain a target radiation noise frequency change chart corresponding to each partial power spectrogram;
and obtaining the Doppler frequency offset amplitude according to the difference between the maximum value and the minimum value in each target radiation noise frequency change graph.
In one embodiment, when the sonar buoys are screened according to the doppler frequency shift amplitude, the first several sonar buoys with the largest doppler frequency shift amplitude are selected as the screened sonar buoys according to the preset number of the sonar buoys.
In one embodiment, the calculating according to the detection signals corresponding to the screening sonar buoys, to obtain the closest distance between the target and each screening sonar buoy in the traveling process, the time corresponding to the closest distance, and the movement speed of the target include:
selecting any two moments from the power spectrograms corresponding to the screening sonar buoys as a first moment and a second moment respectively, and correspondingly acquiring a first frequency and a second frequency corresponding to the two moments respectively;
recording a line spectrum frequency change curve in each corresponding power spectrogram, solving an inflection point on the line spectrum frequency change curve, and obtaining a third time and a third frequency corresponding to the inflection point, wherein the third time and the third frequency are respectively the time and the frequency of the nearest distance of a target to a sonar buoy;
and calculating by adopting a positioning formula 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 spectrogram to obtain the nearest distance between the target and each screening sonar buoy and the corresponding target movement speed respectively.
In one embodiment, the positioning formula is expressed as:
wherein ,Δt 1 ＝T cpa -t 1 ，Δt 2 ＝T cpa -t 2
in the above formula, D represents the nearest distance between the target and the sonar buoy, v represents the moving speed of the target at the nearest distance, and t 1 、t 2 、T cpa Respectively representing the first time, the second time and the third time, F 1 、F 2 、f cpa The first frequency, the second frequency, and the third frequency are respectively represented.
In one embodiment, calculating the lengths of the common tangent lines of each group according to the corresponding tangent points of the common tangent lines, and scoring the lengths of the common tangent lines of each group by using a secondary scoring mechanism includes:
scoring twice the common tangent lines in each group in sequence, wherein the first scoring comprises: calculating theoretical length and actual length of the public tangent line in each group according to the coordinates of the tangent points, comparing the theoretical length and the actual length of the public tangent line with a preset difference range according to the difference value of the theoretical length and the actual length of the public tangent line, adding 1 score to the corresponding public tangent line if the difference value is within the preset difference range, and adding 0 score to the corresponding public tangent line if the difference value is not within the preset difference range;
the second scoring includes: and calculating the distance from the tangent point of the second circle in the circle of the former group to the tangent point of the first circle in the circle of the latter group, wherein the common tangent line corresponding to the smallest distance is added by 1 minute.
In one embodiment, the fitting the possible track scattered points of the target to obtain the estimated motion track of the target includes:
and fitting possible track scattered points of the target by adopting a polynomial fitting method to obtain an estimated motion track of the target.
In one embodiment, the fitting the possible track scattered points of the target to obtain the estimated motion track of the target includes:
filtering possible track scattered points of the target by adopting a moving average method or a Kalman filtering method to obtain more accurate track scattered points;
and fitting the filtered motion trail scattered points by adopting the polynomial fitting method to obtain the estimated motion trail of the target.
A target trajectory estimation device based on a passive omnidirectional sonar buoy, the device comprising:
the detection signal acquisition module is used for acquiring a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in the passive omnidirectional sonar buoys;
the sonar buoy screening module is used for processing each detection signal to obtain Doppler frequency offset amplitude of the corresponding sonar buoy relative to the target, and screening the sonar buoy according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys closest to the target;
The nearest distance parameter calculation module is used for calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance between the target and each screening sonar buoy in the travelling process, the time corresponding to the nearest distance and the movement speed of the target;
the circular construction module is used for constructing a plurality of circles by taking the coordinates of each screening sonar buoy as the circle center and taking the corresponding nearest distance as the radius, and then calculating a common tangent line and a corresponding tangent point of two circles with adjacent arrival time as a group according to the time of the arrival of the target at the nearest distance from each screening sonar buoy;
the possible track scattered point obtaining module is used for calculating the lengths of the common tangent lines of each group according to the corresponding tangent points of the common tangent lines, scoring the lengths of the common tangent lines of each group by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent lines with the highest score in each group of circles as the possible track scattered points of the target;
and the motion track estimation fitting module is used for fitting possible track scattered points of the target to obtain an estimated motion track of the target.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
Acquiring a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in passive omnidirectional sonar buoys;
processing each detection signal to obtain Doppler frequency offset amplitude of a corresponding sonar buoy relative to the target, and screening the sonar buoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys nearest to the target;
calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance between the target and each screening sonar buoy in the advancing process, the corresponding time when the nearest distance is reached and the movement speed of the target;
taking the coordinates of each screening sonar buoy as a circle center, constructing a plurality of circles by taking the corresponding nearest distance as a radius, and calculating a common tangent line and a corresponding tangent point of each circle with two circles with adjacent arrival time as a group according to the time of the target reaching the nearest distance from each screening sonar buoy;
calculating the length of each group of common tangent lines according to the corresponding tangent points of the common tangent lines, respectively scoring the length of each group of common tangent lines by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent line with the highest score in each group of circles as possible track scattered points of the target;
And fitting possible track scattered points of the target to obtain an estimated motion track of the target.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in passive omnidirectional sonar buoys;
processing each detection signal to obtain Doppler frequency offset amplitude of a corresponding sonar buoy relative to the target, and screening the sonar buoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys nearest to the target;
calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance between the target and each screening sonar buoy in the advancing process, the corresponding time when the nearest distance is reached and the movement speed of the target;
taking the coordinates of each screening sonar buoy as a circle center, constructing a plurality of circles by taking the corresponding nearest distance as a radius, and calculating a common tangent line and a corresponding tangent point of each circle with two circles with adjacent arrival time as a group according to the time of the target reaching the nearest distance from each screening sonar buoy;
Calculating the length of each group of common tangent lines according to the corresponding tangent points of the common tangent lines, respectively scoring the length of each group of common tangent lines by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent line with the highest score in each group of circles as possible track scattered points of the target;
and fitting possible track scattered points of the target to obtain an estimated motion track of the target.
According to the target track estimation method, device and equipment based on the passive omnidirectional sonar buoys, the multiple sonar buoys closest to the target in the passive omnidirectional sonar buoys are screened, detection signals corresponding to the screened sonar buoys are processed to obtain the closest distance between the target and each screened sonar buoy and the time and the movement speed corresponding to the closest distance between the target and each screened sonar buoy, then the coordinates of each screened buoy are used as the circle centers, the closest distance is used as the radius to construct multiple circles, the two circles with the close arrival time are used as a group to calculate the length of a common tangent line, then a secondary scoring mechanism is used to obtain the common tangent line with the highest score in each group of circles, the corresponding tangent point coordinates are used as possible track points of the target, and finally the obtained multiple track points are fitted to obtain the estimated movement track of the target.
Drawings
FIG. 1 is a flow chart of a target trajectory estimation method based on a passive omni-directional sonar buoy in one embodiment;
FIG. 2 is a schematic diagram of the position of a ship and buoy in one embodiment;
FIG. 3 is a flow diagram of a secondary scoring mechanism method in one embodiment;
FIG. 4 is a block diagram of a target trajectory estimation device based on a passive omni-directional sonar buoy in one embodiment;
fig. 5 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
As shown in fig. 1, a target track estimation method based on a passive omnidirectional sonar buoy is provided, which comprises the following steps:
step S100, a detection signal data set is obtained, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in the passive omnidirectional sonar buoys;
step S110, processing each detection signal to obtain Doppler frequency offset amplitude of a corresponding sonar buoy relative to a target, and screening the sonar buoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys closest to the target;
Step S120, calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance of the target from the screening sonar buoys in the advancing process, the corresponding time when the nearest distance is reached and the movement speed of the target;
step S130, constructing a plurality of circles by taking coordinates of each screening sonar buoy as a circle center and taking a corresponding nearest distance as a radius, and calculating a common tangent line and a corresponding tangent point of each circle with two circles with adjacent arrival time as a group according to the time of reaching the nearest distance of the target from each screening sonar buoy;
step S140, calculating the length of each group of common tangent lines according to the corresponding tangent points of the common tangent lines, respectively scoring the length of each group of common tangent lines by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent lines with the highest score in each group of circles as possible track scattered points of the target;
and step S150, fitting possible track scattered points of the target to obtain an estimated motion track of the target.
In this embodiment, the sonar buoy closest to the target in the passive omnidirectional sonar buoy is first screened, and the detection data obtained by the sonar buoy obtained by screening is processed to obtain the closest distance and the corresponding time of the moving target when the moving target passes through the several buoys. And then constructing a circle by taking the coordinates of each screening sonar buoy as the circle center and the nearest distance as the radius, taking two adjacent circles as a group, determining the common tangent and the length of the circles, scoring the common tangent sections of each group of circles by adopting a secondary scoring mechanism, taking the coordinates of the tangent points corresponding to the common tangent of each group of highest scoring points as possible track scattered points of the target, and fitting a plurality of possible track scattered points to obtain the accurate motion track of the target.
In step S100, each sonar buoy in the passive omnidirectional sonar buoy array is a passive omnidirectional sonar buoy, and the target may be a ship running on the water surface or a submarine running on the water bottom. The present method is described herein by way of example in terms of a ship.
In step S110, when the ship (target) passes by the passive omnidirectional sonar buoy array edge, the detected data obtained by all the sonar buoys in the passive omnidirectional sonar buoy array are not valuable as references, and all the detected data do not need to be processed, so that in order to improve efficiency and accuracy, only the detected signals of a plurality of sonar buoys, which are closest to the target passing by the sonar buoy array, need to be processed, and therefore, in the method, the sonar buoys are screened by adopting the doppler frequency offset amplitude, and the detected data with larger offset amplitude are selected for subsequent processing.
In this embodiment, processing each detection signal to obtain the doppler frequency shift amplitude of the corresponding sonar buoy relative to the target includes: and respectively carrying out short-time Fourier transform on each detection signal to obtain a corresponding power spectrogram, and intercepting each power spectrogram according to a preset target center frequency to obtain a part of power spectrogram. Then, carrying out quadratic curve interpolation on the spectrum value corresponding to each moment in each partial power spectrogram to obtain a peak value, and selecting a frequency point corresponding to the peak value as a target radiation noise frequency measurement value at the corresponding moment. And smoothing all the target radiation noise frequency measured values in each part of the power spectrograms by adopting a five-point three-time smoothing method to obtain target radiation noise frequency change graphs corresponding to each part of the power spectrograms, and finally obtaining Doppler frequency offset amplitude according to the difference between the maximum value and the minimum value in each target radiation noise frequency change graph.
Specifically, first, the center frequency of the ship is selected. And selecting partial power spectrograms within a certain range according to the center frequency. Then, because the detected data are discrete, the sample point obtained by obtaining the peak value of the detected signal is often not a local maximum value, but a true local maximum value is needed to be obtained by interpolation between two adjacent sample points, in the method, a quadratic curve (parabola) method is adopted for interpolation, the LOFAR (power spectrum) spectrum value at each moment is subjected to quadratic curve interpolation to obtain the peak value, and then the frequency point with the maximum amplitude is selected as the ship radiation noise frequency measurement value at the moment. And finally, smoothing all the ship radiation noise frequency measured values by adopting a five-point three-time smoothing method to obtain a predicted ship radiation noise frequency change diagram. Because the extracted frequency change curve is not smooth enough, a five-point three-time smoothing method is adopted for smoothing, the five-point three-time smoothing method is a three-time least square polynomial smoothing processing method for discrete data by utilizing a least square method, and the difference between the maximum value and the minimum value of the smoothed frequency change curve is obtained to obtain the Doppler frequency offset amplitude.
Specifically, let the sequence x (N), n=1, 2,..n, y (N) be the output of x (N) after five-point three-time smoothing, the calculation formula of the five-point three-time smoothing method is:
in this embodiment, when the sonar buoys are screened according to the doppler frequency shift amplitude, the first several sonar buoys with the largest doppler frequency shift amplitude are selected as the screened sonar buoys according to the preset number of the sonar buoys.
Next, in step S120, a new positioning method is provided, including: and selecting any two moments as a first moment and a second moment respectively in the power spectrograms corresponding to each screening sonar buoy, correspondingly acquiring a first frequency and a second frequency corresponding to the two moments respectively, simultaneously recording a line spectrum frequency change curve in each corresponding power spectrogram, obtaining an inflection point on the line spectrum frequency change curve, and obtaining a third time and a third frequency corresponding to the inflection point, wherein the third time and the third frequency are respectively the time and the frequency of the target reaching the nearest distance from the sonar buoy. And calculating by adopting a positioning formula 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 spectrogram to obtain the nearest distance between the target and each screening sonar buoy and the corresponding target movement speed respectively.
Further, the positioning formula is expressed as:
wherein ,Δt 1 ＝T cpa -t 1 ，Δt 2 ＝T cpa -t 2
in the formulas (2) and (3), D represents the nearest distance of the target from the sonar buoy, v represents the moving speed of the target at the nearest distance, and t 1 、t 2 、T cpa Respectively representing the first time, the second time and the third time, F 1 、F 2 、f cpa The first frequency, the second frequency, and the third frequency are respectively represented.
Specifically, because the ship radiation noise LOFAR spectrogram has a narrow-band line spectrum component with higher frequency, the ship is continuously approaching to the buoy and then is far away, according to the Doppler effect, the LOFAR line of the buoy signal can move from high to low, the closest point of the buoy and the target is CPA (closest point of approach), and the position diagram of the ship and the buoy is shown in fig. 2.
According to the Doppler frequency shift formula, the line spectrum frequency detected by the buoy is as follows:
in the formula (4), f represents the measured target frequency, f represents the center frequency of the ship, v represents the running speed of the ship,and c represents the underwater sound speed.
Selecting two moments t in LOFAR spectrogram 1 、t 2 The frequencies of (2) are F respectively 1 、F 2 From equation (4):
when the ship is from approaching the buoy to being far away from the buoy, the LOFAR line spectrum frequency is reduced (from being greater than the ship target center frequency to being smaller than the ship target center frequency), the LOFAR line spectrum frequency change is recorded, and the inflection point of the line spectrum curve is obtained, so that the frequency f of the ship target reaching the CPA point can be obtained cpa And time T cpa 。
And (3) making: Δt (delta t) 1 ＝T cpa -t 1 ，Δt 2 ＝T cpa -t 2 。
From equation (4):
f cpa ＝f 0 (7)
the two sides of the formula (8) and the formula (9) are squared and then simplified, and the following steps are carried outThen equation (2) and equation (3) can be derived. In both equations, t 1 、t 2 、y 1 、y 2 V and D can be obtained by known methods.
The novel target positioning method based on Doppler analysis, which is proposed herein, uses time information, t to be measured 1 、t 2 、F 1 、F 2 、T cpa 、f cpa Is relatively easy to obtain and does not require two observation points to be point symmetric about the CPA.
Next, in steps S130 and S140, by calculating and scoring the length of the common tangent, a more accurate ship track point is obtained.
Specifically, the positions of the buoys are used as circle centers, the distance D between the closest points of the buoys and the ship targets is used as a radius to make circles, and two circles with adjacent arrival time are used as a group to calculate a common tangent line and a corresponding tangent point according to the time that the ship arrives at the closest distance from each screening sonar buoy.
Let the equation for two adjacent circles be:
C 1 :(x-x 1 ) 2 +(y-y 1 ) 2 ＝r 1 2 (10)
C 2 :
in the formula (10) and the formula11 In (x) 1 ,y 1 )、(x 2 ,y 2 ) Respectively are circles C 1 、C 2 Center of circle, r 1 、r 2 Respectively are circles C 1 、C 2 Is set with:
Δ + ＝(x 1 -x 2 ) 2 +(y 1 -y 2 ) 2 -(r 1 +r 2 ) 2 (12)
Δ - ＝(x 1 -x 2 ) 2 +(y 1 -y 2 ) 2 -(r 1 -r 2 ) 2 (13)
q＝x 1 y 2 -x 2 y 1 (16)
the equation of the common tangent to get the two circles is as follows:
according to the position relation between two adjacent circles, four public tangent lines can be obtained at most from each group of circles.
Specifically, the first scoring includes: and respectively calculating the theoretical length and the actual length of the public tangent line according to the coordinates of the tangent points in each group, comparing the theoretical length and the actual length of the public tangent line with a preset difference range according to the difference value of the theoretical length and the actual length of the public tangent line and the actual length, adding 1 score to the corresponding public tangent line if the difference value is within the preset difference range, and adding 0 score to the corresponding public tangent line if the difference value is not within the preset difference range.
The second scoring includes: and calculating the distance from the tangent point of the second circle in the circle of the former group to the tangent point of the first circle in the circle of the latter group, wherein the common tangent line corresponding to the smallest distance is added by 1 minute.
Specifically, the secondary scoring mechanism is processed according to the flow shown in fig. 3. First scoring mechanism: the tangential length is calculated by tangential point coordinates on each group of circles, then tangential point speed (calculated according to uniform acceleration or uniform deceleration) and time difference are calculated by a novel method based on Doppler analysis, so that theoretical tangential length can be obtained, then the theoretical tangential point length and the theoretical tangential point speed are compared, a difference threshold value is set, a voting mechanism is adopted, if the corresponding public tangential line is marked with 1 score in the difference range, the public tangential line is marked with 0 score in the range, then each public tangential line is marked with a plurality of circles to be tangent, and all public tangential lines are marked with the public tangential line.
The second scoring mechanism: and calculating the distance from the tangent point of the second circle in the previous group of circles to the tangent point of the first circle in the next group of circles, and adding one minute to the tangent line corresponding to the minimum distance. And selecting the tangent line with the highest score in each group of circles according to a twice scoring mechanism, wherein the tangent point on the tangent line with the highest score is used as a predicted ship movement track point.
After the possible track scattered points of the ship are obtained, in step S150, error analysis is performed on all the obtained track scattered points which are possible to be targets, and then the track is fitted to obtain a track equation.
In this embodiment, after singular values are removed from the located scattered points, a polynomial fitting method, a moving average method, or a kalman filtering method is used, and a locating point error confidence coefficient prediction boundary under a preset confidence probability is also calculated, where the confidence range is calculated by adopting the following formula:
in equation (21), b is the coefficient generated by fitting, t depends on the confidence probability and uses the inverse of the t cumulative distribution function, S is the vector of diagonal elements in the estimated covariance matrix of the coefficient estimation, (X) T X) -1 s 2 . In the linear fitting, X is the design matrix, while for the nonlinear fitting, X is the jacobian of the fit value versus the coefficient, X T Is the transpose of X, s 2 Is the mean square error.
In the method, one of a polynomial fitting method, a moving average method or a Kalman filtering method is adopted to conduct error analysis, or the three methods are adopted to conduct error analysis simultaneously.
Specifically, when error analysis is performed on the scattered points by using a polynomial fitting method, coefficients of the polynomial p (x) of degree n are returned, and the order is the best fit (in the least square method) of the data in y. The coefficients in p are arranged in power reduction, and the length of p is n+1:
p(x)＝p 1 x n +p 2 x n-1 +…+p n x+p n+1 (22)
specifically, when performing error analysis by using a moving average method (moving average), the moving average method (moving average) is a signal smoothing method in the time domain concept. The algorithm thinking is that sampling points near the point are calculated and averaged as a value after the point is smooth. The general window is a symmetrical window, preventing phase deviation. The window is generally odd, taking the 3-point average (window length is 3) formula as an example, the original data is x, and the smoothed data is y:
and smoothing the data by adopting a moving average function, and moving the window with a fixed length to obtain an average value in each window.
Specifically, when the Kalman filtering method is adopted to perform error analysis, kalman filtering is mainly used for optimally estimating the state of the system through two processes of prediction and update. The core process formula is as follows:
The state prediction equation is:
in equation (24), F is a state transition matrix,is the optimal estimated value of the state at the last moment, B is a control matrix, u t-1 Is the system control amount at the last moment. Prediction error covariance matrix:
P t - ＝FP t-1 F T +Q (25)
in formula (25), P t-1 And Q is a state noise covariance matrix for the estimation error covariance matrix of the last moment. The kalman gain matrix K under the optimal estimation condition is:
K t ＝P t - H T (HP t - H T +R) -1 (26)
in the above formula (26), H is a control matrix of the observation matrix, and R is an observation covariance matrix. The state update equation is:
in the above formula (27), z t To observe the matrix.
Estimating an error covariance matrix:
p t ＝(1-K t H)P t - (28)
in practice, if the polynomial fitting method is adopted to fit the moving track scattered points, the moving track equation and the confidence coefficient prediction boundary of the target can be directly obtained. When the other two methods are adopted, a moving average method or a Kalman filtering method is required to filter possible track scattered points of the target to obtain more accurate track scattered points, and then a polynomial fitting method is adopted to fit the filtered motion track scattered points to obtain an estimated motion track of the target.
According to the target track estimation method based on the passive omnidirectional sonar buoy, doppler frequency offset is automatically searched in a wider frequency spectrum interval of a LOFAR spectrogram, a quadratic curve interpolation peak value solving method is adopted to extract a frequency change curve, a five-point three-time smoothing method is adopted to carry out smoothing treatment on the frequency change curve, doppler frequency offset of each sonar buoy is automatically calculated, and buoys participating in Doppler-CPA positioning are automatically given out by comparing with the offset proportion of each sonar buoy. And obtaining possible positioning points of the target by adopting a twice scoring mechanism. First scoring mechanism: scoring is performed by a voting mechanism using the theoretical tangential length and the actual tangential length. The second scoring mechanism: and calculating the distance between tangent points on the two adjacent groups of circles, and adding one division to the corresponding tangent line with the smallest distance. And selecting the tangent line with the highest score in each group of circles according to a twice scoring mechanism, wherein the tangent point on the tangent line with the highest score is the possible locating point of the target. And finally estimating the motion trail of the target through three error estimation models, namely a polynomial fitting method, a moving average method and a Kalman filtering method. By adopting the method, the track of the target can be positioned more accurately.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
In one embodiment, as shown in fig. 4, there is provided a target track estimating device based on a passive omni-directional sonar buoy, including: a detection signal acquisition module 200, a sonar buoy screening module 210, a nearest distance parameter calculation module 220, a circular construction module 230, a possible track scattered point obtaining module 240 and an estimated motion estimation fitting module 250, wherein:
the detection signal acquisition module 200 is configured to acquire a detection signal data set, where the detection signal data set includes a plurality of detection signals obtained by passively detecting a target by each sonar buoy in the passive omnidirectional sonar buoys;
The sonar buoy screening module 210 is configured to process each of the detection signals to obtain a doppler frequency shift amplitude of a corresponding sonar buoy relative to the target, and screen the sonar buoy according to the doppler frequency shift amplitude to obtain a plurality of screened sonar buoys closest to the target;
the nearest distance parameter calculation module 220 is configured to calculate according to the detection signals corresponding to the screening sonar buoys, so as to obtain the nearest distance between the target and each screening sonar buoy in the traveling process, the time corresponding to the nearest distance, and the movement speed of the target;
the circle construction module 230 is configured to construct a plurality of circles with coordinates of each of the screened sonar buoys as a center of a circle and with a corresponding nearest distance as a radius, and calculate a common tangent line and a corresponding tangent point of two circles with adjacent arrival times as a group according to the time that the target arrives at the nearest distance from each of the screened sonar buoys;
the possible track scattered point obtaining module 240 is configured to calculate lengths of the common tangent lines of each group according to the tangent points corresponding to the common tangent lines, respectively score the lengths of the common tangent lines of each group by adopting a secondary scoring mechanism, and use coordinates corresponding to the tangent points of the common tangent line with the highest score in each group of circles as possible track scattered points of the target;
The motion track estimation fitting module 250 is configured to fit possible track scattered points of the target to obtain an estimated motion track of the target.
For specific limitations of the passive omni-directional sonar buoy-based target trajectory estimation device, reference may be made to the above limitations of the passive omni-directional sonar buoy-based target trajectory estimation method, and details thereof are not repeated herein. The modules in the target track estimation device based on the passive omnidirectional sonar buoy can be all or partially realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured 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 operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by the processor is used for realizing a target track estimation method based on the passive omnidirectional sonar buoy. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
acquiring a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in passive omnidirectional sonar buoys;
processing each detection signal to obtain Doppler frequency offset amplitude of a corresponding sonar buoy relative to the target, and screening the sonar buoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys nearest to the target;
calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance between the target and each screening sonar buoy in the advancing process, the corresponding time when the nearest distance is reached and the movement speed of the target;
Taking the coordinates of each screening sonar buoy as a circle center, constructing a plurality of circles by taking the corresponding nearest distance as a radius, and calculating a common tangent line and a corresponding tangent point of each circle with two circles with adjacent arrival time as a group according to the time of the target reaching the nearest distance from each screening sonar buoy;
calculating the length of each group of common tangent lines according to the corresponding tangent points of the common tangent lines, respectively scoring the length of each group of common tangent lines by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent line with the highest score in each group of circles as possible track scattered points of the target;
and fitting possible track scattered points of the target to obtain an estimated motion track of the target.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in passive omnidirectional sonar buoys;
processing each detection signal to obtain Doppler frequency offset amplitude of a corresponding sonar buoy relative to the target, and screening the sonar buoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys nearest to the target;
Calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance between the target and each screening sonar buoy in the advancing process, the corresponding time when the nearest distance is reached and the movement speed of the target;
taking the coordinates of each screening sonar buoy as a circle center, constructing a plurality of circles by taking the corresponding nearest distance as a radius, and calculating a common tangent line and a corresponding tangent point of each circle with two circles with adjacent arrival time as a group according to the time of the target reaching the nearest distance from each screening sonar buoy;
calculating the length of each group of common tangent lines according to the corresponding tangent points of the common tangent lines, respectively scoring the length of each group of common tangent lines by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent line with the highest score in each group of circles as possible track scattered points of the target;
and fitting possible track scattered points of the target to obtain an estimated motion track of the target.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile 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. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. The target track estimation method based on the passive omnidirectional sonar buoy is characterized by comprising the following steps of:
acquiring a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in passive omnidirectional sonar buoys;
processing each detection signal to obtain Doppler frequency offset amplitude of a corresponding sonar buoy relative to the target, and screening the sonar buoys according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys nearest to the target;
Calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance between the target and each screening sonar buoy in the advancing process, the corresponding time when the nearest distance is reached and the movement speed of the target;
taking the coordinates of each screening sonar buoy as a circle center, constructing a plurality of circles by taking the corresponding nearest distance as a radius, and calculating a common tangent line and a corresponding tangent point of each circle with two circles with adjacent arrival time as a group according to the time of the target reaching the nearest distance from each screening sonar buoy;
calculating the length of each group of common tangent lines according to the corresponding tangent points of the common tangent lines, respectively scoring the length of each group of common tangent lines by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent line with the highest score in each group of circles as possible track scattered points of the target;
and fitting possible track scattered points of the target to obtain an estimated motion track of the target.
2. The method of claim 1, wherein the processing each of the detection signals to obtain a doppler frequency shift magnitude of a corresponding sonar buoy relative to the target comprises:
Respectively carrying out short-time Fourier transform on each detection signal to obtain a corresponding power spectrogram, and intercepting each power spectrogram according to a preset target center frequency to obtain a part of power spectrogram;
performing quadratic curve interpolation on the spectrum value corresponding to each moment in each partial power spectrogram to obtain a peak value, and selecting a frequency point corresponding to the peak value as a target radiation noise frequency measurement value at the corresponding moment;
smoothing all the target radiation noise frequency measured values in each partial power spectrogram by adopting a five-point three-time smoothing method to obtain a target radiation noise frequency change chart corresponding to each partial power spectrogram;
and obtaining the Doppler frequency offset amplitude according to the difference between the maximum value and the minimum value in each target radiation noise frequency change graph.
3. The target track estimation method according to claim 2, wherein when the sonar buoys are screened according to the doppler frequency shift amplitude, the first several sonar buoys with the largest doppler frequency shift amplitude are selected as the screened sonar buoys according to a preset number of sonar buoys.
4. The method of estimating a target track according to claim 3, wherein the calculating according to the detection signals corresponding to the screening sonar buoys, to obtain the nearest distance of the target from each screening sonar buoy during traveling, the corresponding time when the nearest distance is reached, and the moving speed of the target include:
Selecting any two moments from the power spectrograms corresponding to the screening sonar buoys as a first moment and a second moment respectively, and correspondingly acquiring a first frequency and a second frequency corresponding to the two moments respectively;
recording a line spectrum frequency change curve in each corresponding power spectrogram, solving an inflection point on the line spectrum frequency change curve, and obtaining a third time and a third frequency corresponding to the inflection point, wherein the third time and the third frequency are respectively the time and the frequency of the nearest distance of a target to a sonar buoy;
and calculating by adopting a positioning formula 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 spectrogram to obtain the nearest distance between the target and each screening sonar buoy and the corresponding target movement speed respectively.
5. The target trajectory estimation method of claim 4, wherein the positioning equation is expressed as:
wherein ,Δt 1 ＝T cpa -t 1 ，Δt 2 ＝T cpa -t 2
in the above formula, D represents the nearest distance between the target and the sonar buoy, v represents the moving speed of the target at the nearest distance, and t 1 、t 2 、T cpa Respectively representing the first time, the second time and the third time, F 1 、F 2 、f cpa The first frequency, the second frequency, and the third frequency are respectively represented.
6. The method of claim 5, wherein calculating the lengths of the common tangent lines of each group according to the corresponding tangent points of the common tangent lines, and scoring the lengths of the common tangent lines of each group by using a secondary scoring mechanism comprises:
scoring twice the common tangent lines in each group in sequence, wherein the first scoring comprises: calculating theoretical length and actual length of the public tangent line in each group according to the coordinates of the tangent points, comparing the theoretical length and the actual length of the public tangent line with a preset difference range according to the difference value of the theoretical length and the actual length of the public tangent line, adding 1 score to the corresponding public tangent line if the difference value is within the preset difference range, and adding 0 score to the corresponding public tangent line if the difference value is not within the preset difference range;
the second scoring includes: and calculating the distance from the tangent point of the second circle in the circle of the former group to the tangent point of the first circle in the circle of the latter group, wherein the common tangent line corresponding to the smallest distance is added by 1 minute.
7. The method of claim 6, wherein the fitting the possible track scatter points of the target to obtain the estimated motion track of the target comprises:
And fitting possible track scattered points of the target by adopting a polynomial fitting method to obtain an estimated motion track of the target.
8. The method of claim 6, wherein the fitting the possible track scatter points of the target to obtain the estimated motion track of the target comprises:
filtering possible track scattered points of the target by adopting a moving average method or a Kalman filtering method to obtain more accurate track scattered points;
and fitting the filtered motion trail scattered points by adopting the polynomial fitting method to obtain the estimated motion trail of the target.
9. Target track estimation device based on passive qxcomm technology sonar buoy, characterized by, the device includes:
the detection signal acquisition module is used for acquiring a detection signal data set, wherein the detection signal data set comprises a plurality of detection signals obtained by passively detecting a target by each sonar buoy in the passive omnidirectional sonar buoys;
the sonar buoy screening module is used for processing each detection signal to obtain Doppler frequency offset amplitude of the corresponding sonar buoy relative to the target, and screening the sonar buoy according to the Doppler frequency offset amplitude to obtain a plurality of screened sonar buoys closest to the target;
The nearest distance parameter calculation module is used for calculating according to detection signals corresponding to the screening sonar buoys to obtain the nearest distance between the target and each screening sonar buoy in the travelling process, the time corresponding to the nearest distance and the movement speed of the target;
the circular construction module is used for constructing a plurality of circles by taking the coordinates of each screening sonar buoy as the circle center and taking the corresponding nearest distance as the radius, and then calculating a common tangent line and a corresponding tangent point of two circles with adjacent arrival time as a group according to the time of the arrival of the target at the nearest distance from each screening sonar buoy;
the possible track scattered point obtaining module is used for calculating the lengths of the common tangent lines of each group according to the corresponding tangent points of the common tangent lines, scoring the lengths of the common tangent lines of each group by adopting a secondary scoring mechanism, and taking the coordinates corresponding to the tangent points of the common tangent lines with the highest score in each group of circles as the possible track scattered points of the target;
and the motion track estimation fitting module is used for fitting possible track scattered points of the target to obtain an estimated motion track of the target.
10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 8 when the computer program is executed.
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