Distributed moving target passive positioning method and system based on deep sea multipath time delay combination

Abstract

The invention discloses a distributed moving target passive positioning method and system based on deep sea multipath time delay combination, and belongs to the technical field of deep sea target detection and positioning. In order to solve the problems that Doppler compensation and multipath time delay combined processing cannot be considered at the same time and a special positioning scheme for a moving target is lacked in the prior art, two hydrophone nodes horizontally arranged near the seabed are utilized; relative Doppler and multipath delay inequality information of radiation signals of a moving target reaching two hydrophone nodes through different propagation paths are combined, a multipath propagation geometrical relationship positioning model of the moving target is constructed by combining a spatial position relationship between the moving target and the hydrophone nodes, and the model is optimized and solved, so that the positioning precision of the moving target is improved. And continuous high-precision positioning of a moving target track is realized. According to the method, the huge calculated amount of matching field processing is avoided, the positioning precision is high, simple, efficient and robust positioning is realized, and the engineering applicability is remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of deep-sea target detection and positioning, and particularly relates to a distributed moving target passive positioning method and system based on deep-sea multi-path time delay combination. BACKGROUND

[0002] In the deep-sea environment, how to achieve robust passive positioning of moving targets using a limited number of underwater acoustic sensors under unknown target source signal waveform conditions has always been a core challenge in the field of underwater acoustics. Existing deep-sea passive positioning technologies usually rely on arrays composed of high-pressure hydrophones to receive target radiated noise and achieve positioning and tracking by estimating and processing signal parameters such as time delay difference, multi-path time delay, and angle of arrival. Although traditional methods have high accuracy in ideal environments, they often require large-aperture vertical line arrays (VLA) and a large number of sensors, resulting in a large system size, complex deployment, and high cost. More importantly, current deep-sea passive positioning research is designed only for stationary targets or assumes that the signal characteristics of the target remain unchanged within a detection frame, without fully considering the Doppler effect caused by target motion, resulting in a significant decline in positioning performance for moving targets.

[0003] In recent years, scholars have focused on the utilization of multi-path time delay information, such as multi-path time delay matching technology based on cross-correlation of dual hydrophones. Lei Zhixiong proposed a positioning method using vertically placed dual hydrophones in "Passive localization in the deep ocean based on cross-correlation function matching" in 2016, which estimates the sound source position by cross-correlation function matching. However, this method is only applicable to stationary targets and has a large computational load, making it unable to handle the Doppler frequency offset caused by target motion. In addition, the current mainstream method combines multi-path time delay information with matched field processing (MFP), such as the deep-sea cross-sound zone sound source positioning method using dual hydrophones disclosed in Chinese patent CN 119044890B. This method only uses two distributed hydrophones, but the positioning results require the calculation of the entire study area's matching sound field, which is computationally complex and does not address the Doppler compensation problem, making it difficult to apply to moving targets. At the same time, MFP-type methods are highly sensitive to environmental parameters and require global sound field matching, resulting in high computational complexity and a lack of effective utilization of the Doppler effect of moving targets, leading to insufficient positioning robustness in practical applications.

[0004] In summary, the prior art cannot simultaneously consider Doppler compensation and multi-path time delay joint processing, especially lacks a special positioning scheme for moving targets, limiting its reliability and engineering application value in deep sea moving target positioning. Therefore, there is an urgent need for a distributed positioning method that can be easily deployed in a deep sea environment, which can jointly process Doppler effect and accurately estimate multi-path time delay to improve the adaptability and computational efficiency of moving targets. SUMMARY

[0005] In view of the above problems, the present application aims to provide a deep sea multi-path time delay joint based distributed passive positioning method and system for moving targets, which utilizes two horizontally distributed near-seabed hydrophone nodes, jointly processes relative Doppler compensation and multi-path time delay difference information, combines the spatial geometric position relationship between the moving target and the two hydrophone nodes, constructs a moving target position model containing the position of the moving target and the different path lengths of the moving target to the two hydrophone nodes, and optimizes and solves the moving target position model to achieve high-precision and unambiguous positioning of the moving target.

[0006] To achieve the above purpose, the technical scheme adopted by the present application is as follows: On the one hand, the present application provides a deep sea multi-path time delay joint based distributed passive positioning method for moving targets, which comprises the following steps: A position coordinate system of the distributed hydrophone nodes is constructed using two horizontally distributed hydrophone nodes, and a signal reception model of the hydrophone nodes receiving the radiation signals of the moving target is established; One of the hydrophone nodes is set as a reference node, and the radiation signals of the moving target received by the reference node are resampled and compensated based on the relative Doppler compensation between the two hydrophone nodes and the signal reception model, and are recorded as reference signals; The reference signals and the radiation signals of the moving target received by the other hydrophone node are cross-correlated, a cross-correlation function model in the relative Doppler-time delay domain is established, and the relative time delay differences of different path combinations between the two hydrophone nodes are extracted; The spatial position relationship between the moving target and the two hydrophone nodes, and the relative time delay differences of different path combinations are combined to construct a moving target multi-path propagation geometric relationship positioning model, and the moving target multi-path propagation geometric relationship positioning model is solved to determine the position of the moving target; The continuous signals of the moving target are processed in time sequence frames to obtain the continuous positioning of the position of the moving target.

[0007] Further, the signal reception model of the hydrophone nodes receiving the radiation signals of the moving target is: ; In the formula, k represents the hydrophone node index, and takes 1 or 2, k takes 1 to represent the first hydrophone node, that is, node H1, and k takes 2 to represent the second hydrophone node, that is, node H2; represents the radiation signal of the moving target received by the hydrophone node k at time t; p represents the path index of the radiation signal of the moving target, and P represents the total number of paths of the radiation signal of the moving target; represents the amplitude value of the pth path of the radiation signal of the moving target arriving at the hydrophone node k; s represents a broadband random signal of the moving target radiation; represents the propagation time delay of the pth path of the radiation signal of the moving target arriving at the hydrophone node k, is the ambient noise; is the Doppler factor.

[0008] Further, based on the relative Doppler compensation between the two hydrophone nodes and the signal receiving model of the hydrophone nodes receiving the radiation signal of the moving target, the radiation signal of the moving target received by the reference node is resampled and compensated, including the following steps: According to the speed range of the moving target, a set of relative Doppler compensation factors between the two hydrophone nodes is constructed; The set of relative Doppler compensation factors is grid divided according to the resolution to generate compensation slices; Based on the compensation slices of the relative Doppler compensation factors, the radiation signal of the moving target received by the reference node is resampled and compensated, and is recorded as a reference signal.

[0009] Further, the reference signal is: ; In the formula, is the reference signal, represents the radiation signal of the moving target received by the first hydrophone node; is the relative Doppler compensation value corresponding to the rth compensation slice in the set of relative Doppler compensation factors, and r represents the index of the compensation slice.

[0010] Further, the reference signal and the radiation signal of the moving target received by the other hydrophone node are cross-correlated to establish a cross-correlation function model in the relative Doppler-time delay domain, and the relative time delay difference between different path combinations of the two hydrophone nodes is extracted, including the following steps: The reference signal and the radiation signal of the moving target received by node H2 are cross-correlated to establish a cross-correlation function model in the relative Doppler-time delay domain ; The cross-correlation function model in the relative Doppler-time delay domain is maximized As the primary optimization objective, determine the optimal solution for the primary optimization objective; Based on the optimal solution of the first optimization objective, the relative time delay difference between different path combinations between two hydrophone nodes is extracted.

[0011] Furthermore, the cross-correlation function model in the relative Doppler-time-delay domain for: ; In the formula, This represents the conjugate of the radiation signal from the moving target received by node H2. This represents the time delay difference between the radiated signals from the moving target received by the two hydrophone nodes.

[0012] Furthermore, combining the spatial relationship between the moving target and the two hydrophone nodes, as well as the relative time delay difference of different path combinations, a multipath propagation geometric relationship localization model for the moving target is constructed. Solving this model determines the position of the moving target, including the following steps: Calculate the path length of the radiated signal from the moving target to the two hydrophone nodes through different propagation paths; Construct a multipath propagation geometric relationship localization model for a moving target that includes the relationship between the position of the moving target and the positions of two hydrophone nodes; Minimize the norm of the geometric relationship localization model for multipath propagation of moving targets as the second optimization objective. Use the Gauss-Newton method to iteratively solve the second optimization objective to determine the position of the moving target.

[0013] Furthermore, the geometric relationship localization model for multipath propagation of a moving target is as follows: ; In the formula, This represents the estimation of the time delay difference between two hydrophone nodes. The residual function between the calculated path length difference and the actual path length difference, where c is the velocity of sound waves in water. This represents the relative time delay difference between the radiation signal of a moving target reaching node H1 via the i-th propagation path and the radiation signal of a moving target reaching node H2 via the j-th propagation path. for The measured values ​​are: Ci represents the i-th propagation path of the radiation signal of the moving target to node H1, and Cj represents the j-th propagation path of the radiation signal of the moving target to node H2. This represents the path length of the moving target to node H1 via propagation path Ci. This represents the path length from the moving target to node H2 via the propagation path Cj; The position parameter vector of the moving target; a horizontal distance of the moving target to the coordinate origin O, an azimuth angle of the moving target, a depth of the moving target, and T is a transpose of a matrix.

[0014] In another aspect, the present application provides a positioning system for deep-sea moving targets based on joint estimation of Doppler compensation and multi-path time delay, which is used to implement the passive positioning method for distributed moving targets based on joint deep-sea multi-path time delay as described above, and the system comprises: a signal collection module: two horizontally distributed hydrophone nodes are used to construct a position coordinate system of the distributed hydrophone nodes, and a signal receiving model of the hydrophone nodes receiving the radiation signals of the moving target is established; a signal processing module: based on the relative Doppler compensation between the two hydrophone nodes and the signal receiving model, the radiation signals of the moving target received by the reference node are resampled and compensated, and a reference signal is output; a positioning solution module: the correlation function model in the relative Doppler-time delay domain is established by performing cross-correlation operation on the reference signal and the radiation signals of the moving target received by the other hydrophone node, and the relative time delay difference of different path combinations between the two hydrophone nodes is extracted; a positioning model of the multi-path propagation geometry relationship of the moving target is constructed and solved to determine the position of the moving target; a display output module: the continuous signals of the moving target are processed in time sequence and in frames, and the continuous positioning and display of the trajectory of the moving target are realized.

[0015] In another aspect, the present application also provides an electronic device, which comprises at least one processor; and a memory connected in communication with the processor; wherein the memory stores instructions executed by the processor, and the instructions are executed by the processor to enable the processor to execute the passive positioning method for distributed moving targets based on joint deep-sea multi-path time delay as described above.

[0016] The present application has the following beneficial effects: 1. The passive positioning method for distributed moving targets based on joint deep-sea multi-path time delay in the present application uses two horizontally distributed hydrophone nodes near the seabed, and through joint relative Doppler compensation and multi-path time delay difference information, combined with the spatial geometric position relationship between the moving target and the two hydrophone nodes, a moving target position model containing the position of the moving target and the different path lengths of the moving target to the two hydrophone nodes is constructed, and the moving target position model is optimized and solved to realize high-precision and non-ambiguous positioning of the moving target. The method innovatively uses the relative Doppler effect generated by the moving target in the movement process, aligns the signals between the two hydrophone nodes through Doppler compensation technology, improves the accuracy of time delay estimation, and overcomes the limitations of the prior art assuming a stationary target.

[0017] 2、The application utilizes the time delay difference of four different path combinations, combines the sound wave propagation path, constructs a moving target position model containing the position of the moving target and the different path length difference of the moving target to the two hydrophone nodes, solves the moving target position model to determine the position of the moving target, avoids the huge calculation amount of the matching field processing, realizes simple and efficient and robust positioning, reduces the calculation amount, and only needs two hydrophone nodes, is suitable for real-time processing, significantly improves the engineering applicability, is suitable for deep sea reliable acoustic path (RAP) scene, is not sensitive to environmental parameter changes, and can improve the positioning reliability in complex propagation environment. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 It is a flowchart of the distributed moving target passive positioning method based on deep sea multi-path time delay combination in the application. Figure 2 It is a schematic diagram of the spatial position relationship between the hydrophone node and the moving target in the application. Figure 3 It is a relative time delay difference estimation result diagram of different path combinations in the sound source starting moment in the experimental scene verification of the application. Figure 4 It is a relative time delay difference error estimation result diagram of different path combinations in the experimental scene verification of the application. Figure 5 It is a continuous positioning result diagram of the sound source in the experimental scene verification of the application. Figure 6 It is a sound source distance estimation and sound source distance relative error result diagram in 20 continuous frames in the experimental scene verification of the application. Figure 7 It is a sound source depth estimation and sound source depth relative error result diagram in 20 continuous frames in the experimental scene verification of the application. DETAILED DESCRIPTION

[0019] In order for those skilled in the art to better understand the technical solutions of the application, the technical solutions of the application will be further described below in combination with the drawings and examples.

[0020] Example one: referring to the drawings Figure 1 The application embodiment provides a distributed moving target passive positioning method based on deep sea multi-path time delay combination, which comprises the following steps: Step 1: using two horizontally distributed hydrophone nodes, constructing a position coordinate system of the distributed hydrophone nodes, establishing a signal receiving model of the hydrophone nodes receiving the radiation signal of the moving target; Specifically, referring to the drawings Figure 2As shown, two hydrophone nodes are respectively denoted as node H1 and node H2, both of which are close to the sea bottom and horizontally distributed, with the sea level projection of the position of node H1 as the coordinate origin O, the direction from node H1 to node H2 as the positive direction of the X axis, the vertical direction of the X axis at the coordinate origin O as the Y axis direction, and the vertical direction of the sea bottom at the coordinate origin O as the positive direction of the Z axis, to establish a Cartesian coordinate system O-XYZ, then the coordinate point of node H1 is ( ), and the coordinate point of node H2 is ( ), wherein, is the depth of node H1, is the depth of node H2, is the horizontal distance between node H1 and node H2. , and are all known. The position parameter of the moving target at time t is , wherein is the horizontal distance of the moving target to the coordinate origin O, is the azimuth angle of the moving target, is the depth of the moving target.

[0021] Assuming that the broadband random signal radiated by the moving target is s, the bandwidth of the broadband random signal is B, and the center frequency of the broadband random signal is . The moving target moves at a speed v, then the received signal of the moving target by node H1 and node H2, that is, the signal receiving model of the hydrophone node receiving the radiation signal of the moving target is: (1) In the formula, k represents the index of the hydrophone node, taking values of 1 or 2, k taking 1 represents node H1, and k taking 2 represents node H2; represents the received radiation signal of the moving target by the hydrophone node k at time t; p represents the path index of the moving target radiation signal, and P represents the total number of paths of the moving target radiation signal; represents the amplitude value of the pth path of the moving target radiation signal arriving at the hydrophone node k; represents the propagation delay of the pth path of the moving target radiation signal arriving at the hydrophone node k, is the environmental noise (assuming to be Gaussian white noise); is the Doppler factor, which is determined by the radial velocity of the moving target relative to the hydrophone node k.

[0022] Due to the deep sea multi-path effect, the radiation signal of the moving target received by each hydrophone node contains multiple propagation path components, in the present application, the direct wave D and the first sea surface reflected wave SR with higher energy are preferred as the propagation path, that is, the total number P of the propagation path of the radiation signal of the moving target is 2, p = 1 or 2, and p = 1 represents that the propagation path of the radiation signal of the moving target is the direct wave, and p = 2 represents that the propagation path of the radiation signal of the moving target is the first sea surface reflected wave.

[0023] For different propagation paths, due to the difference in the radial velocity of the moving target relative to different hydrophone nodes, the received signals of the moving target by the nodes H1 and H2 are different. Thus, there is a relative Doppler between the received signals of the moving target by the nodes H1 and H2. which reflects the signal compression or expansion caused by the movement of the moving target, and the expression is: (2) In the formula, c is the speed of sound in water, represents the radial velocity of the moving target relative to the hydrophone node k on the pth path.

[0024] Step 2: Set one of the hydrophone nodes as a reference node, and resample and compensate the received signal of the moving target by the reference node based on the relative Doppler compensation between the two hydrophone nodes and the signal receiving model, and record it as the reference signal; Optionally, step 2 includes the following sub-steps: Sub-step 201: According to the speed range of the moving target, a set of relative Doppler compensation factors between the two hydrophone nodes is constructed; Specifically, in order to align the received signals of the moving target by the two hydrophone nodes in the time domain, it is necessary to compensate the relative Doppler between the different hydrophone nodes. Taking the node H1 as the reference node, according to the possible speed range of the moving target (the movement speed of the moving target under water is usually ±4.5 m / s, wherein + represents that the moving target moves towards the direction close to the hydrophone node, and — represents that the moving target moves away from the hydrophone node), the movement speed of the moving target observed by the node H2 relative to the movement speed range of the moving target observed by the reference node is set as wherein v min represents the minimum value of the movement speed of the moving target observed by the node H2 relative to the movement speed of the moving target observed by the reference node, and v max represents the maximum value of the movement speed of the moving target observed by the node H2 relative to the movement speed of the moving target observed by the reference node. The set of relative Doppler compensation factors is calculated by formula (2) wherein is the minimum value of the relative Doppler compensation factor, is the maximum value of the relative Doppler compensation factor, , is the maximum value of the relative Doppler compensation factor, is the maximum value of the relative Doppler compensation factor, .

[0025] Sub-step 202: grid division is performed on the set of relative Doppler compensation factors according to the resolution, to generate compensation slices; The set of relative Doppler compensation factors is grid divided according to the resolution to generate compensation slices, which are used for subsequent Doppler resampling. If the resolution is 0.0001, then is divided into 10000 compensation slices.

[0026] Sub-step 203: resampling and compensation are performed on the radiation signal of the moving target received by the reference node based on the compensation slices of the relative Doppler compensation factor, and the signal is recorded as the reference signal; Before resampling and compensation are performed, the radiation signal of the moving target received by the node H1 and the node H2 needs to be filtered and preprocessed for noise reduction. The signal obtained after resampling and compensation of the radiation signal of the moving target received by the reference node based on the compensation slices of the relative Doppler compensation factor is recorded as the reference signal, and the reference signal is represented as: (3) In the formula, is the reference signal, represents the radiation signal of the moving target received by the first hydrophone node; is the relative Doppler compensation value corresponding to the rth compensation slice in the set of relative Doppler compensation factors, and r represents the index of the compensation slice.

[0027] Through the operation, a set of reference signals of the moving target under different relative Doppler compensation values can be further constructed, which are used for relative Doppler compensation domain search.

[0028] Step 3: cross-correlation operation is performed on the reference signal and the radiation signal of the moving target received by another hydrophone node, a cross-correlation function model in the relative Doppler-delay domain is established, and the relative delay difference of different path combinations between the two hydrophone nodes is extracted; Optionally, step 3 includes the following sub-steps: Sub-step 301: cross-correlation operation is performed on the reference signal and the radiation signal of the moving target received by the node H2, and a cross-correlation function model in the relative Doppler-delay domain is established , which is specifically represented as: (4) wherein, denotes the conjugate of the received signal of the moving target by node H2, is the time delay difference of the received signals of the moving target by the two hydrophone nodes.

[0029] Sub-step 302: maximizing the cross-correlation function model of the relative Doppler-time delay domain as the first optimization objective, and determining the optimal solution of the first optimization objective; Specifically, when the moving target reaches the two hydrophone nodes through different propagation paths, the time delay difference of the received signals of the moving target by the two hydrophone nodes is different, and therefore, the cross-correlation function model of the relative Doppler-time delay domain is maximized as the first optimization objective, the set of relative Doppler compensation factors and the time delay difference are searched, and the optimal solution of the first optimization objective is determined, that is, the relative Doppler compensation factor estimation and the relative time delay difference estimation between the two hydrophone nodes under the condition that the cross-correlation function model of the relative Doppler-time delay domain is maximized : (5) wherein, denotes the relative time delay difference between the received signal of the moving target by the i-th propagation path to node H1 and the received signal of the moving target by the j-th propagation path to node H2, i=1 or 2, j=1 or 2, and the values of i and j are 1, which represents that the propagation path of the received signal of the moving target is a direct wave, or 2, which represents that the propagation path of the received signal of the moving target is a once sea surface reflected wave.

[0030] Sub-step 303: based on the optimal solution of the first optimization objective, that is, the relative Doppler compensation factor estimation and the time delay difference estimation between the two hydrophone nodes , the relative time delay differences of different path combinations between the two hydrophone nodes are extracted; based on the relative Doppler compensation factor estimation and the time delay difference estimation between the two hydrophone nodes , the relative time delay differences of four different path combinations are extracted: ; ; ; ; wherein, This represents the relative time delay difference between the arrival time of the radiated signal of the moving target at node H1 via the direct wave and the arrival time of the radiated signal of the moving target at node H2 via the direct wave. The time delay of the radiated signal from the moving target reaching node H1 via the direct wave. The time delay between the arrival of the radiated signal of the moving target at node H2 via the direct wave; This represents the relative time delay difference between the arrival of the radiated signal of a moving target at node H1 via a direct wave and the arrival of the radiated signal of a moving target at node H2 via a first-order sea surface reflected wave. The time delay for the radiation signal of a moving target to reach node H2 via a single sea surface reflection wave; This represents the relative time delay difference between the arrival of the radiated signal of a moving target at node H1 via a first-order sea surface reflected wave and the arrival of the radiated signal of the moving target at node H2 via a direct wave; The time delay for the radiation signal of a moving target to reach node H1 via a single sea surface reflection wave; This represents the relative time delay difference between the arrival of the radiated signal of the moving target at node H1 via a first sea surface reflection wave and the arrival of the radiated signal of the moving target at node H2 via a first sea surface wave.

[0031] Step 4: Combining the spatial relationship between the moving target and the two hydrophone nodes, as well as the relative time delay difference of different path combinations, construct a multipath propagation geometric relationship localization model for the moving target, solve the multipath propagation geometric relationship localization model for the moving target, and determine the position of the moving target; Optionally, step 4 includes the following sub-steps: Sub-step 401: Calculate the path length of the radiated signal of the moving target to the two hydrophone nodes through different propagation paths; Specifically, based on the position of the moving target, the position of node H1, and the position of node H2 at time t, the path lengths of the radiated signal from the moving target reaching nodes H1 and H2 through different paths are calculated, as follows: (6) In the formula, Let H1 be the path length of the radiated signal from the moving target reaching node H1 via the direct wave. Let H1 be the path length of the radiated signal from the moving target reaching node H1 via a first sea surface reflection wave. Let H2 be the path length of the radiated signal from the moving target reaching node H2 via the direct wave. Let H2 be the path length of the radiated signal from the moving target reaching node H2 via a first sea surface reflection wave. The horizontal distance between the moving target and node H1. The horizontal distance between the moving target and node H2.

[0032] Sub-step 402: Construct a multipath propagation geometric relationship localization model for the moving target, which includes the relationship between the position of the moving target and the positions of the two hydrophone nodes; Using the Law of Cosines, and and The relationship can be obtained as follows: (7) The relative time delay difference and the path length difference satisfy the following: (8) In the formula, Ci and Cj represent different paths (D or SR), Ci represents the i-th propagation path of the radiation signal of the moving target to node H1, and Cj represents the j-th propagation path of the radiation signal of the moving target to node H2. This represents the path length of the moving target to node H1 via propagation path Ci. This represents the path length of the moving target to node H2 via the propagation path Cj.

[0033] Based on the time delay difference estimation between two hydrophone nodes Construct a multipath propagation geometric relationship localization model for a moving target, which includes the relationship between the position of the moving target and the positions of the two hydrophone nodes: (9) In the formula, This represents the estimation of the time delay difference between two hydrophone nodes. The residual function between the calculated path length difference and the actual path length difference. Let T be the position parameter vector of the moving target, and T be the transpose of the matrix. Substituting formula (7) into formula (9) will yield the position parameter vector of the moving target.

[0034] Sub-step 403: Minimize the norm of the multipath propagation geometric relationship localization model of the moving target as the second optimization objective. Use the Gauss-Newton method to iteratively solve the second optimization objective to determine the position of the moving target. Specifically, minimizing the norm of the moving target's position model is the second optimization objective, that is: (10) Solving the second optimization objective using the Gauss-Newton iterative method yields the following results: (11) Where n represents the number of iterations, which is a non-negative integer, and n=0,1,2,…, n=0 corresponds to the initial solution of the second optimization objective, that is, the initial position of the moving target.

[0035] In deep-sea positioning scenarios, the initial solution for the second optimization objective can be set using prior knowledge or simple geometric relationships. For example, the initial horizontal distance r0 of the moving target can be set as r 1,2 Half of the time difference or a rough calculation based on the time delay difference (such as using the single-path time delay difference) (Approximate relationship with distance). The initial azimuth angle φ0 can be set to 0° or estimated based on the direction angle of the line connecting the two hydrophone nodes. The initial depth z0 can be set to half the sea depth or based on a priori depth of the sound source. Jacobian matrix. The elements are calculated using partial derivatives, iterating until convergence (e.g.) , ), outputs the position of the moving target at time t.

[0036] Step 5: Perform time-series frame-segmentation processing on the continuous signal of the moving target to obtain the continuous positioning of the moving target's position.

[0037] Specifically, the continuous signal of the moving target is processed by time-series framing, with each frame having a length of 10 seconds. Steps 2-4 are repeated for each frame, and the position parameters of the moving target in that time sequence can be obtained. .

[0038] State tracking is performed on the position parameters of a moving target across consecutive frames. Considering the motion characteristics of the moving target in three-dimensional space, a state vector is defined. for: (12) in, for rate of change, for rate of change, for The rate of change.

[0039] The state transition model for the moving target is then: (13) In the formula, Let be the state vector of the moving target at time t. Let be the state vector of the moving target at time t-1. Here is the state transition matrix. Z is the sampling interval (frame length 10s); w t It has a mean of zero and a covariance of Process noise.

[0040] Define observation model for: (14) in, The observation model at time t; For the observation matrix, , It has a mean of zero and a covariance of Observation noise.

[0041] Kalman filtering is used to fuse the state transition model and observation model of a moving target, enabling continuous tracking of the target's position. The specific process of fusing the state transition model and observation model of a moving target using Kalman filtering includes the following steps: (1) Initialization: The localization result of the moving target's position in the first frame is used as the initial state estimate. ,but Then the initial error covariance , It is a 6-dimensional identity matrix.

[0042] (2) Prediction phase (state update): State prediction: (15) In the formula, Let t be the predicted state value of the moving target. The state value of the moving target at time t-1; Error covariance prediction: (16) In the formula, Let be the predicted value of the error covariance at time t. Let be the error covariance at time t-1.

[0043] (3) Update phase (measurement update): Calculate Kalman gain : (17) Status Update: (18) In the formula, Let be the state update value of the moving target at time t. Let t be the predicted state value of the moving target at time t.

[0044] Error covariance update: (19) In the formula, Let be the updated value of the error covariance at time t. Let be the predicted value of the error covariance at time t.

[0045] In this process, the covariance of process noise It can be set according to the motion characteristics of the moving target: (20) Where q is the process noise intensity, which is set according to the maximum acceleration of the moving target. For underwater moving targets, it is usually reasonably set to 5.

[0046] The covariance R of the observation noise is set as follows: (twenty one) in, The standard deviation of the distance observation error. The standard deviation of the observation error of the azimuth angle. This represents the standard deviation of the depth observation error.

[0047] After Kalman filtering, the final smooth trajectory of the moving target is output as follows: (twenty one) In the formula, for The estimated value, for The estimated value, for The estimated value.

[0048] Experimental Scenario Verification: The positioning method described in this invention was used for experimental verification in a sea area of ​​the South China Sea. Data acquisition was conducted using a buoy system with two hydrophone nodes. Nodes H1 and H2 were deployed at depths of 1851m and 1679m respectively, with a horizontal spacing of 5400m, and a sampling rate of 4kHz. The seabed in the experimental area was flat, with an average depth of 2100m.

[0049] See attached document Figure 2 A coordinate system for the distributed hydrophone nodes is constructed, with the sea-level projection of node H1 as the origin O. The direction from node H1 to node H2 is the positive X-axis, the direction perpendicular to the X-axis at the origin O within the sea level is the Y-axis, and the direction perpendicular to the seabed from the origin O is the positive Z-axis. A Cartesian coordinate system O-XYZ is established. The coordinates of node H1 are (0, 0, 1851) m, and the coordinates of node H2 are (5400, 0, 1679) m. The moving target (sound source) is a broadband transmitter at a calibration depth of 103 m. The initial coordinates of the moving target are (1512, 1102, 103) m, and the azimuth angle φ = 12.5°. The following section uses the signal from the sound source at the initial moment as an example to demonstrate the complete sound source localization method.

[0050] Using node H1 as the reference node, and setting the velocity range of the sound source to ±4.5 m / s based on the motion characteristics of the sound source, the observed velocity range of node H2 relative to node H1 is [-9, 9] m / s. The set of relative Doppler compensation factors is calculated using formula (2). The received signal at node H1 is resampled and compensated to establish a cross-correlation function model in the relative Doppler-time delay domain. The model that maximizes the cross-correlation function in the relative Doppler-time delay domain is shown in the appendix. Figure 3 As shown, the relative time delay difference between the four path combinations between two hydrophone nodes is extracted as follows: τ 1,1 = -1194.25ms; τ 2,1 = -952.5ms; τ 1,2 = -1440.5ms; τ 2,2 = -1199.25ms.

[0051] Substituting the relative time delay difference of the four path combinations between the two hydrophone nodes into formulas (6)-(11), and using the Gauss-Newton method for iterative solution, the estimated target position at the initial time is (1481,1158,102) m. Compared with the actual position, the distance error is 31 m (relative error 2.05%), and the depth error is 1 m (relative error 0.97%).

[0052] The continuous signal emitted by the sound source is processed in frames (frame length 10s), and the above steps are repeated to obtain multi-frame localization results. The trajectory is smoothed by Kalman filtering using formulas (12) and (13), as shown in the attached figure. Figure 5 The image shows a continuous spatial trajectory of a moving target. Figure 4 The display shows the relative time delay difference error results of different path combinations of 20 consecutive frames of signals, providing reliable data support for positioning.

[0053] The localization method of this invention was used to continuously process the radiation signal of the sound source for 20 consecutive frames, and the final continuous trajectory localization result is shown in the attached figure. Figure 6 and attached Figure 7 As shown, in the appendix Figure 6 In the image, (a) shows the estimated distance of the sound source (distance from the origin of the coordinate system in the horizontal direction) for 20 consecutive frames; (b) shows the relative error of the sound source distance for the corresponding 20 consecutive frames. It can be seen that as the sound source moves away from the origin of the coordinate system, the relative error of its distance estimation is consistently less than 2%, and the absolute error of the distance estimation is consistently less than 35m, indicating high positioning accuracy. (See attached image.) Figure 7 In the image, (a) shows the estimated depth of the sound source over 20 consecutive frames; (b) shows the relative error of the sound source depth over the corresponding 20 consecutive frames. (See attached image.)Figure 7 As can be seen, during the process of the sound source moving away from the origin of the coordinate system, the relative error of its depth estimation is always less than 3%, and the absolute error of its distance estimation is always less than 3m.

[0054] Experimental results verify the high accuracy and stability of the positioning method in this invention for continuous positioning of moving targets.

[0055] Example 2: This example provides a positioning system for deep-sea moving targets based on Doppler compensation and multipath delay joint estimation. The system is used to implement the distributed passive positioning method for deep-sea moving targets based on deep-sea multipath delay joint estimation described in Example 1.

[0056] Specifically, the system includes: Signal acquisition module: Using two horizontally distributed hydrophone nodes, a position coordinate system of the distributed hydrophone nodes is constructed, and a signal reception model for the hydrophone nodes to receive the radiated signals of moving targets is established; in specific implementation, the two hydrophone nodes adopt a pressure-resistant packaging design and have an operating depth greater than 5000m; it supports a 4kHz sampling rate and 100-600Hz bandpass filtering.

[0057] Signal processing module: Based on the relative Doppler compensation between the two hydrophone nodes and the signal receiving model, the radiation signal of the moving target received by the reference node is resampled and compensated, and a reference signal is output. The positioning calculation module performs cross-correlation calculations on the reference signal and the radiation signal of the moving target received by another hydrophone node, establishes a cross-correlation function model in the relative Doppler-time delay domain, extracts the relative time delay difference between different path combinations between the two hydrophone nodes, and constructs and solves the moving target position model. The display output module performs time-series frame processing on the continuous signal of the moving target to obtain the time-series position result of the moving target. It then uses Kalman filtering to fuse the time-series position result of the moving target to achieve continuous trajectory positioning of the moving target.

[0058] This application also provides an electronic device, including at least one processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, which, when executed by the processor, enable the processor to perform the distributed passive localization method for moving targets based on deep-sea multipath delay joint as described in Embodiment 1. The processor is a multi-core DSP processor with a main frequency of 1.2 GHz; the memory uses 8 GB RAM and 512 GB solid-state storage; the operating system can be an embedded Linux system.

[0059] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for passive localization of a moving target based on deep sea multi-path time delay combination, characterized in that, The method comprises the following steps: A position coordinate system of the distributed hydrophone nodes is constructed by using two horizontally distributed hydrophone nodes, and a signal receiving model of the hydrophone nodes receiving the radiation signal of the moving target is established; One of the hydrophone nodes is set as a reference node, and the radiation signal of the moving target received by the reference node is resampled and compensated based on the relative Doppler compensation between the two hydrophone nodes and the signal receiving model, and is recorded as a reference signal; The reference signal and the radiation signal of the moving target received by the other hydrophone node are subjected to cross-correlation operation, a cross-correlation function model in the relative Doppler-delay domain is established, and the relative delay difference between different path combinations of the two hydrophone nodes is extracted; The position of the moving target is determined by constructing a moving target multipath propagation geometric relationship positioning model based on the spatial position relationship between the moving target and the two hydrophone nodes and the relative delay difference of different path combinations, and solving the moving target multipath propagation geometric relationship positioning model. The position of the moving target is continuously positioned by performing time sequence frame processing on the continuous signal of the moving target.

2. The method according to claim 1, wherein, The signal receiving model of the hydrophone nodes receiving the radiation signal of the moving target is: ； In the formula, k represents the hydrophone node index, and takes the value of 1 or 2, k takes 1 to represent the first hydrophone node, that is, node H1, and k takes 2 to represent the second hydrophone node, that is, node H2; represents the radiation signal of the moving target received by the hydrophone node k at time t; p represents the path index of the moving target radiation signal, and P represents the total number of paths of the moving target radiation signal; represents the amplitude value of the pth path of the moving target radiation signal reaching the hydrophone node k; s represents the broadband random signal of the moving target radiation; represents the propagation delay of the pth path of the moving target radiation signal reaching the hydrophone node k, is the ambient noise; is the Doppler factor.

3. The method according to claim 2, wherein, The radiation signal of the moving target received by the reference node is resampled and compensated based on the relative Doppler compensation between the two hydrophone nodes and the signal receiving model of the hydrophone nodes receiving the radiation signal of the moving target, comprising the following steps: A set of relative Doppler compensation factors between the two hydrophone nodes is constructed according to the speed range of the moving target; The set of relative Doppler compensation factors is grid divided according to the resolution to generate a compensation slice; The radiation signal of the moving target received by the reference node is resampled and compensated based on the compensation slice of the relative Doppler compensation factor, and is recorded as a reference signal.

4. The method according to claim 3, wherein, The reference signal is: ； In the formula, is a reference signal, represents the radiation signal of the moving target received by the first hydrophone node; is the relative Doppler compensation value corresponding to the rth compensation slice in the set of relative Doppler compensation factors, and r represents the index of the compensation slice.

5. The method according to claim 4, wherein, The reference signal and the radiation signal of the moving target received by the other hydrophone node are subjected to cross-correlation operation, a cross-correlation function model in the relative Doppler-delay domain is established, and the relative delay difference between different path combinations of the two hydrophone nodes is extracted, comprising the following steps: Correlate the radiation signals of the motion target received by the reference signal and the node H2 to establish a correlation function model in the relative Doppler-time delay domain ; Maximizing a cross-correlation function model over the relative doppler-delay domain as a first optimization objective, determining an optimal solution for the first optimization objective; The relative delay difference between different path combinations of the two hydrophone nodes is extracted based on the optimal solution of the first optimization target.

6. The method according to claim 5, wherein, Relative doppler-time delay domain cross-correlation function model is: ； wherein denotes the conjugate of the received radiated signal of the moving target by the node H2, is the time delay difference of the received radiated signal of the moving target by the two hydrophone nodes.

7. The method according to claim 6, wherein, The position of the moving target is determined by constructing a moving target multipath propagation geometric relationship positioning model based on the spatial position relationship between the moving target and the two hydrophone nodes and the relative delay difference of different path combinations, and solving the moving target multipath propagation geometric relationship positioning model, comprising the following steps: The path lengths of the radiation signal of the moving target passing through different propagation paths to reach the two hydrophone nodes are calculated; A moving target multipath propagation geometric relationship positioning model containing the position relationship between the moving target and the two hydrophone nodes is constructed; The norm of the moving target multipath propagation geometric relationship positioning model is minimized as a second optimization target, and the Gauss-Newton method is used to iteratively solve the second optimization target to determine the position of the moving target.

8. The method according to claim 7, wherein, The moving target multipath propagation geometric relationship positioning model is: ； wherein, denotes the relative time delay difference between the radiation signal of the moving target arriving at node H1 through the i-th propagation path and the radiation signal of the moving target arriving at node H2 through the j-th propagation path, the residual function of the calculated path length difference and the true path length difference, c is the sound speed in water, denotes the relative time delay difference between the radiation signal of the moving target arriving at node H1 through the i-th propagation path and the radiation signal of the moving target arriving at node H2 through the j-th propagation path, is the measurement value of Ci represents the i-th propagation path of the radiation signal of the moving target arriving at node H1, and Cj represents the j-th propagation path of the radiation signal of the moving target arriving at node H2; denotes the path length of the moving target arriving at node H1 through the propagation path Ci, denotes the path length of the moving target arriving at node H2 through the propagation path Cj; is the position parameter vector of the moving target; is the horizontal distance of the moving target to the coordinate origin O, is the azimuth angle of the moving target, is the depth of the moving target, and T is the transpose of the matrix.

9. A positioning system for deep-sea moving targets based on joint Doppler compensation and multi-path time delay estimation, for implementing the method for passive positioning of distributed moving targets based on joint deep-sea multi-path time delay estimation according to any one of claims 1 to 8, characterized in that, The system comprises: The signal acquisition module: two horizontally distributed hydrophone nodes are used to build a position coordinate system of the distributed hydrophone nodes, and a signal receiving model of the hydrophone nodes receiving the radiation signal of the moving target is established; The signal processing module: based on the relative Doppler compensation between the two hydrophone nodes and the signal receiving model, the radiation signal of the moving target received by the reference node is resampled and compensated, and the reference signal is output; The positioning calculation module: the correlation function model of the relative Doppler-time delay domain is established by performing cross-correlation operation on the reference signal and the radiation signal of the moving target received by another hydrophone node, and the relative time delay difference of different path combinations between the two hydrophone nodes is extracted; a moving target multi-path propagation geometric relationship positioning model is constructed and solved to determine the position of the moving target; The display output module: the continuous signal of the moving target is processed by time sequence frame, and the continuous positioning and display of the trajectory of the moving target are realized.

10. An electronic device, comprising: The electronic device includes at least one processor; and a memory connected with the processor in communication; wherein the memory stores instructions executed by the processor, and the instructions are executed by the processor to enable the processor to execute the deep-sea multi-path time delay joint-based distributed moving target passive positioning method of any one of claims 1-8.

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