A deep-sea multi-path time delay combined distributed moving target passive positioning method and system

Abstract

The application discloses a kind of based on deep sea multi-path time delay joint distributed moving target passive positioning method and system, belong to deep sea target detection and positioning technical field.For the prior art cannot simultaneously consider Doppler compensation and multi-path time delay joint processing, lack of special positioning scheme for moving target and other problems, the present application utilizes two hydrophone nodes horizontally laid in near seabed, the relative Doppler and multi-path time delay difference information of the radiation signal of moving target combined with different propagation paths to reach two hydrophone nodes, combined with the spatial position relationship between moving target and hydrophone node, the multi-path propagation geometric relationship positioning model of moving target is constructed, and the model is optimized and solved, realize the continuous high-precision positioning of moving target trajectory.The method avoids the huge amount of calculation of matching field processing, and has high positioning accuracy, realizes simple, efficient and robust positioning, and significantly improves the engineering applicability.

Description

Technical Field

[0001] This invention relates to the field of deep-sea target detection and positioning technology, and in particular to a distributed passive positioning method and system for moving targets based on deep-sea multipath time delay joint. Background Technology

[0002] In deep-sea environments, achieving robust passive localization of moving targets using a limited number of underwater acoustic sensors under unknown target source signal waveforms has always been a core challenge in the field of underwater acoustics. Existing deep-sea passive localization technologies typically rely on arrays of high-pressure-resistant hydrophones to receive target radiated noise and achieve localization and tracking by estimating and processing signal parameters (such as time delay difference, multipath delay, and angle of arrival). While traditional methods achieve high accuracy in ideal environments, they often require large-aperture vertical linear arrays (VLAs) and a large number of sensors, resulting in large-scale, complex, and costly systems. More importantly, current deep-sea passive localization research only designs for stationary targets or assumes that the target's signal characteristics remain unchanged within a detection frame, failing to fully consider the Doppler effect caused by target motion, leading to a significant decrease in the localization performance for moving targets.

[0003] In recent years, scholars have focused on utilizing multipath delay information, such as multipath delay matching techniques based on the cross-correlation of two hydrophones. In 2016, Lei Zhixiong proposed a localization method using vertically deployed dual hydrophones in his paper "Passive localization in the deep ocean based on cross-correlation function matching," estimating the sound source location through cross-correlation function matching. However, this method is only applicable to stationary targets, has a high computational cost, and cannot handle Doppler frequency shifts caused by target motion. Furthermore, current mainstream methods combine multipath delay information with matched field processing (MFP). For example, Chinese invention patent CN 119044890B discloses a cross-sound-zone sound source localization method using dual hydrophones in a deep-sea environment. This method utilizes only two distributed hydrophones, but its localization results require calculating the matched sound field of the entire study area, which is computationally complex and does not solve the Doppler compensation problem, making it difficult to apply to moving targets. Meanwhile, MFP-type methods are highly sensitive to environmental parameters and require global sound field matching, resulting in high computational complexity. They also lack effective utilization of the Doppler effect of moving targets, leading to insufficient robustness in localization in practical applications.

[0004] In summary, existing technologies cannot simultaneously address both Doppler compensation and multipath delay joint processing, and particularly lack dedicated positioning schemes for moving targets, limiting their reliability and engineering application value in deep-sea moving target positioning. Therefore, there is an urgent need for a distributed positioning method that is easily deployed in deep-sea environments, capable of jointly processing Doppler effects and accurately estimating multipath delay, in order to improve adaptability to moving targets and computational efficiency. Summary of the Invention

[0005] To address the aforementioned problems, this invention aims to provide a distributed passive positioning method and system for moving targets based on deep-sea multipath delay joint positioning. Utilizing two horizontally distributed near-seabed hydrophone nodes, and by combining relative Doppler compensation and multipath delay difference information, along with the spatial geometric positional relationship between the moving target and the two hydrophone nodes, a moving target position model is constructed, incorporating the moving target's position and different path lengths from the moving target to the two hydrophone nodes. This model is then optimized to achieve high-precision, unambiguous positioning of the moving target.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: On one hand, the present invention provides a distributed passive localization method for moving targets based on deep-sea multipath time delay joint method, the method comprising the following steps: Using two horizontally distributed hydrophone nodes, a position coordinate system for the distributed hydrophone nodes is constructed, and a signal reception model for the hydrophone nodes to receive radiated signals from moving targets is established. One of the hydrophone nodes is set as the reference node. 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 denoted as the reference signal. Cross-correlation calculations are performed on the reference signal and the radiation signal of the moving target received by another hydrophone node to establish a cross-correlation function model in the relative Doppler-time delay domain, and the relative time delay difference between the two hydrophone nodes for different path combinations is extracted. By 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. The position of the moving target is determined by solving the multipath propagation geometric relationship localization model. The continuous signal of the moving target is processed by time-series framing to obtain the continuous positioning of the moving target.

[0007] Furthermore, the signal reception model for the hydrophone node receiving the radiated signal from the moving target is as follows: ; In the formula, k represents the hydrophone node index, which can be 1 or 2. When k is 1, it represents the first hydrophone node, i.e., node H1. When k is 2, it represents the second hydrophone node, i.e., node H2. This represents the radiated signal of the moving target received by hydrophone node k at time t; p represents the path index of the radiated signal of the moving target; and P represents the total number of paths of the radiated signal of the moving target. The amplitude of the moving target's radiated signal reaching the hydrophone node k via the p-th path is represented; s represents the broadband random signal radiated by the moving target. The propagation delay of the p-th path of the radiated signal from the moving target to the hydrophone node k is represented by . For environmental noise; It is the Doppler factor.

[0008] Furthermore, based on the relative Doppler compensation between the two hydrophone nodes and the signal reception 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: Based on the velocity range of the moving target, construct a set of relative Doppler compensation factors between two hydrophone nodes; The set of relative Doppler compensation factors is divided into grids according to resolution to generate compensation slices; 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 denoted as the reference signal.

[0009] Furthermore, the reference signal is: ; In the formula, For reference signal, This represents the radiated signal from the moving target received by the first hydrophone node; Let r be the relative Doppler compensation value corresponding to the r-th compensation slice in the set of relative Doppler compensation factors, where r represents the index of the compensation slice.

[0010] Furthermore, cross-correlation is performed on the reference signal and the radiated signal of the moving target received by another hydrophone node to establish a cross-correlation function model in the relative Doppler-time delay domain. The relative time delay difference between the two hydrophone nodes for different path combinations is extracted, including the following steps: Cross-correlation calculations are performed on the reference signal and the radiation signal from the moving target received by node H2 to establish a cross-correlation function model in the relative Doppler-time delay domain. ; Model for maximizing the cross-correlation function in the relative Doppler-time-delay domain 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; This is the position parameter vector of the moving target; Let O be the horizontal distance from the moving target to the origin O. Let be the azimuth angle of the moving target. Let T be the depth of the moving target, and T be the transpose of the matrix.

[0014] On the other hand, the present invention provides a positioning system for deep-sea moving targets based on Doppler compensation and multipath delay joint estimation, for realizing the distributed passive positioning method for deep-sea moving targets based on deep-sea multipath delay joint estimation as described above. 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. 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 and 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, constructs and solves the multipath propagation geometric relationship positioning model of the moving target, and determines the position of the moving target. Display output module: performs time-series framing processing on the continuous signal of the moving target to achieve continuous positioning and display of the moving target's trajectory.

[0015] In another aspect, the present invention also provides an electronic device, the electronic device including at least one processor; and a memory communicatively connected to the processor; wherein the memory stores instructions to be executed by the processor, the instructions being executed by the processor to enable the processor to execute the distributed moving target passive localization method based on deep-sea multipath delay joint as described above.

[0016] The beneficial effects of this invention are: 1. This invention presents a distributed passive localization method for moving targets based on deep-sea multipath delay co-location. Utilizing two horizontally distributed near-seabed hydrophone nodes, it constructs a moving target position model by combining relative Doppler compensation and multipath delay difference information with the spatial geometric positional relationship between the moving target and the two hydrophone nodes. This model includes the moving target's position and different path lengths from the moving target to the two hydrophone nodes. The method then optimizes and solves this model to achieve high-precision, unambiguous localization of the moving target. This innovative method leverages the relative Doppler effect generated during the moving target's motion, aligning the signals between the two hydrophone nodes through Doppler compensation technology. This improves the accuracy of delay estimation and overcomes the limitations of existing technologies that assume stationary targets.

[0017] 2. This invention utilizes the time delay difference of four different path combinations, combined with the sound wave propagation path, to construct a moving target position model that includes the moving target's position and the different path length differences from the moving target to the two hydrophone nodes. Solving the moving target position model determines the moving target's position, avoiding the massive computational load of matched field processing, achieving simple, efficient, and robust positioning, reducing computational load, and requiring only two hydrophone nodes, making it suitable for real-time processing, significantly improving engineering applicability, applicable to deep-sea reliable acoustic path (RAP) scenarios, insensitive to changes in environmental parameters, and able to improve positioning reliability in complex propagation environments. Attached Figure Description

[0018] Figure 1 This is a flowchart of the distributed passive localization method for moving targets based on deep-sea multipath delay joint method in this invention; Figure 2 This is a schematic diagram showing the spatial relationship between the hydrophone node and the moving target in this invention; Figure 3 This is a graph showing the estimation results of the relative time delay difference for different path combinations at the start time of the sound source in the experimental scenario verification of this invention; Figure 4 This is a graph showing the relative delay difference error estimation results for 20 consecutive frames with different path combinations in the experimental scenario verification of this invention; Figure 5 This is a diagram showing the continuous localization results of the sound source in the experimental scenario verification of this invention; Figure 6 This is a graph showing the results of sound source distance estimation and relative error of sound source distance for 20 consecutive frames in the experimental scenario verification of this invention; Figure 7 The image shows the results of sound source depth estimation and relative error of 20 consecutive frames in the experimental scenario verification of this invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0020] Example 1: Refer to Appendix Figure 1 As shown in the figure, this application provides a distributed passive localization method for moving targets based on deep-sea multipath delay joint method, which includes the following steps: Step 1: Using two horizontally distributed hydrophone nodes, construct a coordinate system for the position of the distributed hydrophone nodes and establish a signal reception model for the hydrophone nodes to receive the radiated signals from moving targets. For details, please refer to the appendix. Figure 2As shown, the two hydrophone nodes are denoted as node H1 and node H2, respectively. Both nodes H1 and H2 are near the seabed and horizontally distributed. Taking 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. Establishing a Cartesian coordinate system O-XYZ, the coordinates of node H1 are (…). The coordinates of node H2 are ( ),in, Let H1 be the depth. The depth of node H2, The horizontal spacing between nodes H1 and H2; , and All are known. The position parameters of the moving target at time t are: ,in Let O be the horizontal distance from the moving target to the origin O. Let be the azimuth angle of the moving target. The depth of the moving target.

[0021] Assume 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 . If the moving target moves at velocity v, then the signal reception model for the radiated signal received by nodes H1 and H2 from the moving target, i.e., the signal received by the hydrophone nodes from the radiated signal of the moving target, is as follows: (1) In the formula, k represents the hydrophone node index, which takes the value of 1 or 2. When k is 1, it represents node H1, and when k is 2, it represents node H2. This represents the radiated signal of the moving target received by hydrophone node k at time t; p represents the path index of the radiated signal of the moving target; and P represents the total number of paths of the radiated signal of the moving target. This represents the amplitude value of the radiated signal from the moving target reaching the hydrophone node k along the p-th path; The propagation delay of the p-th path of the radiated signal from the moving target to the hydrophone node k is represented by . The ambient noise is assumed to be Gaussian white noise. It is the Doppler factor, determined by the radial velocity of the moving target relative to the hydrophone node k.

[0022] Due to the deep-sea multipath effect, the radiation signal of the moving target received by each hydrophone node contains multiple propagation path components. In this invention, the direct wave D with higher energy and the first sea surface reflection wave SR are preferred as propagation paths. That is, the total number of paths P of the radiation signal of the moving target is 2, p=1 or 2, and when p=1, it means that the propagation path of the radiation signal of the moving target is the direct wave, and when p=2, it means that the propagation path of the radiation signal of the moving target is the first sea surface reflection wave.

[0023] For different propagation paths, the radial velocity of the moving target relative to different hydrophone nodes varies, therefore This results in a relative Doppler effect between the radiation signals from the moving target received by nodes H1 and H2. This reflects the signal compression or expansion caused by the motion of a moving target, and is expressed as: (2) In the formula, c is the speed of sound in water. This represents the radial velocity of the moving target relative to the hydrophone node k on the p-th path.

[0024] Step 2: Set one of the hydrophone nodes as the reference node. Based on the relative Doppler compensation between the two hydrophone nodes and the signal reception model, resample and compensate the radiation signal of the moving target received by the reference node, and denote it as the reference signal. Optionally, step 2 includes the following sub-steps: Sub-step 201: Based on the velocity range of the moving target, construct a set of relative Doppler compensation factors between the two hydrophone nodes; Specifically, to align the radiation signals of the moving target received by the two hydrophone nodes in the time domain, relative Doppler compensation is required between the different hydrophone nodes. Taking node H1 as the reference node, based on the possible velocity range of the moving target (the underwater velocity of a moving target is typically ±4.5 m / s, where + indicates the moving target is moving towards the hydrophone node, and - indicates the moving target is moving away from the hydrophone node), the velocity range of the moving target observed by node H2 relative to the velocity observed by the reference node is set as follows: , where v min v represents the minimum velocity of the moving target observed by node H2 relative to the velocity of the moving target observed by the reference node. max This represents the maximum value of the moving target's velocity observed by node H2 relative to the moving target's velocity observed by the reference node. The set of relative Doppler compensation factors is calculated using formula (2). ,in, This represents the minimum value of the relative Doppler compensation factor. This represents the maximum value of the relative Doppler compensation factor. , .set up ,but .

[0025] Sub-step 202: Divide the relative Doppler compensation factor set into a grid according to the resolution to generate compensation slices; Set of relative Doppler compensation factors According to resolution Mesh generation is performed to generate compensation slices for subsequent Doppler resampling. (Resolution) If the value is 0.0001, then... It is divided into 10,000 compensation slices.

[0026] Sub-step 203: Based on the compensation slice of the relative Doppler compensation factor, the radiation signal of the moving target received by the reference node is resampled and compensated, and denoted as the reference signal; Before resampling and compensation, the radiation signals of the moving target received by nodes H1 and H2 need to be filtered and denoised. Taking node H1 as the reference node, the signal obtained after resampling and compensation of the radiation signal of the moving target received by the reference node based on the compensation slice of the relative Doppler compensation factor is denoted as the reference signal. The reference signal is expressed as: (3) In the formula, For reference signal, This represents the radiated signal from the moving target received by the first hydrophone node; Let r be the relative Doppler compensation value corresponding to the r-th compensation slice in the set of relative Doppler compensation factors, where r represents the index of the compensation slice.

[0027] This operation allows for the further construction of a set of reference signals for a moving target under different relative Doppler compensation values. It is used for relative Doppler compensation domain search.

[0028] Step 3: Perform cross-correlation calculation on the reference signal and the radiation signal of the moving target received by another hydrophone node, establish a cross-correlation function model in the relative Doppler-time delay domain, and extract the relative time delay difference between the two hydrophone nodes for different path combinations; Optionally, step 3 includes the following sub-steps: Sub-step 301: Perform cross-correlation calculation on the reference signal and the radiation signal of the moving target received by node H2 to establish a cross-correlation function model in the relative Doppler-time delay domain. Specifically, it is expressed as: (4) 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.

[0029] Sub-step 302: Maximize the cross-correlation function model in the relative Doppler-time delay domain as the first optimization objective, and determine the optimal solution of the first optimization objective; Specifically, when a moving target arrives at two hydrophone nodes via different propagation paths, the time delay difference of the radiated signal received by the two hydrophone nodes from the moving target is different. Therefore, maximizing the cross-correlation function model in the relative Doppler-time delay domain is crucial. As the primary optimization objective, the search is for a set of relative Doppler compensation factors. and latency difference The optimal solution for the first optimization objective is determined, which is to maximize the cross-correlation function model in the relative Doppler-time delay domain. Estimation of relative Doppler compensation factor under the given conditions Estimation of the relative time delay difference between two hydrophone nodes : (5) in, The relative time delay difference between the radiation signal of the moving target reaching node H1 through the i-th propagation path and the radiation signal of the moving target reaching node H2 through the j-th propagation path is represented by i=1 or 2, j=1 or 2. When i and j are both 1, it means that the radiation signal of the moving target is a direct wave, and when i and j are both 2, it means that the radiation signal of the moving target is a first-order sea surface reflected wave.

[0030] Sub-step 303: Estimating the optimal solution based on the first optimization objective, i.e., the relative Doppler compensation factor. Delay difference estimation between two hydrophone nodes Extract the relative time delay difference between different path combinations between two hydrophone nodes; Based on relative Doppler compensation factor estimation Delay difference estimation between two hydrophone nodes Extract the relative delay difference of four different path combinations: ; ; ; ; In the formula, 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 of the moving target from 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 certain sea area, employing a buoy system with two hydrophone nodes for data acquisition. 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. Therefore, 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 the present invention is defined by the appended claims and their equivalents.

Claims

1. A distributed passive localization method for moving targets based on deep-sea multipath time-delay joint localization, characterized in that, The method includes the following steps: Using two horizontally distributed hydrophone nodes, a position coordinate system for the distributed hydrophone nodes is constructed, and a signal reception model for the hydrophone nodes to receive radiated signals from moving targets is established. One of the hydrophone nodes is set as the reference node. 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 denoted as the reference signal. Cross-correlation calculations are performed on the reference signal and the radiation signal of the moving target received by another hydrophone node to establish a cross-correlation function model in the relative Doppler-time delay domain, and the relative time delay difference between the two hydrophone nodes for different path combinations is extracted. By 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. The position of the moving target is determined by solving the multipath propagation geometric relationship localization model. The continuous signal of the moving target is processed by time-series framing to obtain the continuous positioning of the moving target.

2. The distributed passive localization method for moving targets based on deep-sea multipath time delay joint as described in claim 1, characterized in that, The signal reception model for a hydrophone node receiving radiated signals from a moving target is as follows: ； In the formula, k represents the hydrophone node index, which can be 1 or 2. When k is 1, it represents the first hydrophone node, i.e., node H1. When k is 2, it represents the second hydrophone node, i.e., node H2. This represents the radiated signal of the moving target received by hydrophone node k at time t; p represents the path index of the radiated signal of the moving target; and P represents the total number of paths of the radiated signal of the moving target. The amplitude of the moving target's radiated signal reaching the hydrophone node k via the p-th path is represented; s represents the broadband random signal radiated by the moving target. The propagation delay of the p-th path of the radiated signal from the moving target to the hydrophone node k is represented by . For environmental noise; It is the Doppler factor.

3. The distributed passive localization method for moving targets based on deep-sea multipath time delay joint as described in claim 2, characterized in that, Based on the relative Doppler compensation between the two hydrophone nodes and the signal reception 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: Based on the velocity range of the moving target, construct a set of relative Doppler compensation factors between two hydrophone nodes; The set of relative Doppler compensation factors is divided into grids according to resolution to generate compensation slices; 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 denoted as the reference signal.

4. The distributed passive localization method for moving targets based on deep-sea multipath time delay joint as described in claim 3, characterized in that, The reference signal is: ； In the formula, For reference signal, This represents the radiated signal from the moving target received by the first hydrophone node; Let r be the relative Doppler compensation value corresponding to the r-th compensation slice in the set of relative Doppler compensation factors, where r represents the index of the compensation slice.

5. A distributed passive localization method for moving targets based on deep-sea multipath time delay joint as described in claim 4, characterized in that, Cross-correlation is performed on the reference signal and the radiated signal of the moving target received by another hydrophone node to establish a cross-correlation function model in the relative Doppler-time delay domain. The relative time delay difference between the two hydrophone nodes for different path combinations is extracted, including the following steps: Cross-correlation calculations are performed on the reference signal and the radiation signal from the moving target received by node H2 to establish a cross-correlation function model in the relative Doppler-time delay domain. ; Model for maximizing the cross-correlation function in the relative Doppler-time-delay domain 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.

6. The distributed passive localization method for moving targets based on deep-sea multipath time delay joint as described in claim 5, characterized in that, 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.

7. A distributed passive localization method for moving targets based on deep-sea multipath delay joint method according to claim 6, characterized in that, By combining the spatial relationship between the moving target and the two hydrophone nodes, and 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.

8. The distributed passive localization method for moving targets based on deep-sea multipath delay joint method according to claim 7, characterized in that, 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; This is the position parameter vector of the moving target; Let O be the horizontal distance from the moving target to the origin O. Let be the azimuth angle of the moving target. Let T be the depth of the moving target, and T be the transpose of the matrix.

9. A positioning system for deep-sea moving targets based on Doppler compensation and multipath delay joint estimation, used to implement the distributed passive positioning method for deep-sea moving targets based on deep-sea multipath delay joint estimation as described in any one of claims 1-8, characterized in that, 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. 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 and 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, constructs and solves the multipath propagation geometric relationship positioning model of the moving target, and determines the position of the moving target. Display output module: performs time-series framing processing on the continuous signal of the moving target to achieve continuous positioning and display of the moving target's trajectory.

10. An electronic device, characterized in that, The electronic device includes at least one processor; and a memory communicatively connected to the processor; wherein the memory stores instructions that are executed by the processor, the instructions being executed by the processor to enable the processor to perform the distributed passive localization method for moving targets based on deep-sea multipath delay joint as described in any one of claims 1-8.

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