A Method for Analyzing the Dynamic Efficiency of Cooperative Detection of Multi-Static Sonar

Abstract

The present invention proposes a method for analyzing the dynamic effectiveness of multi-static sonar collaborative detection. Step 1): Select a detection area, set multi-static sonar nodes within the detection area, and grid the detection area; Step 2): Calculate the instantaneous detection probability of the sonar at the current moment; Step 3): Calculate the cumulative detection probability of the sonar; Step 4): After the sonar executes the detection task at the current moment, use the prior probability of the target's existence before the sonar executes the detection to calculate the posterior probability of the target's existence; Step 5): Construct a target existence probability transition matrix G and update the prior probability of the target's existence at the next moment; Step 6): Repeat Step 2) to Step 5) until the dynamic detection effectiveness of the sonar within the detection task time is obtained. The present invention analyzes the detection effectiveness of multi-static sonar from multiple dimensions, summarizes the calculation method of cumulative detection probability and the dynamic effectiveness evaluation method according to the sonar detection probability, and analyzes the detection effectiveness of multi-static sonar in the actual detection process from different perspectives.

Description

Technical Field

[0001] The present invention relates to the technical field of sonar detection, and mainly relates to a method for analyzing the dynamic efficiency of multi-static sonar collaborative detection. Background Art

[0002] The problem of underwater target detection is a key issue restricting the improvement of the marine area warning ability. In shallow waters, due to high environmental noise and the increasing "quietness" of underwater targets, the detection range of passive detection is getting closer and closer, and the use of active detection of underwater targets has become a new hotspot. However, in a complex shallow water environment, active sonar will be severely affected by reverberation and false target interference, and its detection ability will also be severely limited. Multi-static sonar has the advantages of concealment, large detection range, high detection and recognition probability, etc., and is one of the effective methods to improve the shallow water detection ability.

[0003] In the domestic research on multi-static sonar, the sonar equations and performance analysis, the composition scheme of multi-static sonar systems, the calculation of multi-static reverberation and target strength have been simulated and calculated respectively. The relationship between the positioning error and structure of multi-static sonar and the optimal receiver structure have been studied, and some experiments have been done to preliminarily verify the feasibility of multi-static detection.

[0004] The analysis and deduction method of multi-static collaborative detection efficiency is the premise and key to efficiently using detection platforms to detect underwater moving targets. Due to the complexity and variability of the marine environment and the strong dependence of sonar detection performance on the marine environment, in multi-static collaborative detection, only relying on the experience of sonar operators or users, there is a lack of scientific quantitative analysis data guidance in the analysis of collaborative underwater detection efficiency, and the detection users lack an understanding of the performance of multi-static collaborative detection, which is mainly manifested in:

[0005] First, in a complex and variable marine environment, it is difficult for users to accurately estimate the detection performance of sonar, resulting in missed information or low efficiency. It is difficult for sonar operators to select appropriate sonar working parameters, resulting in the detection performance of multi-static sonar not being fully exerted.

[0006] Second, the means for evaluating the efficiency of multi-static collaborative detection have an imperfect evaluation model for the detection probability of underwater moving targets. The results of multi-static collaborative detection have a large degree of contingency, and it is also impossible to steadily improve the detection ability of underwater moving targets. Summary of the Invention

[0007] The present invention provides a method for analyzing the dynamic efficiency of multi-static sonar collaborative detection for evaluating the detection efficiency of multi-static sonar in the scenario of regional target detection.

[0008] The object of the present invention is achieved by the following technical solutions. A method for analyzing the dynamic efficiency of multi-static sonar collaborative detection includes the following steps:

[0009] Step 1): Select a detection area, set up multi-static sonar nodes within the detection area, grid the detection area, and initialize the target presence probability.

[0010] Step 2): At the current moment, calculate the instantaneous detection probability of the sonar based on the real-time ocean environment, combat situation, and sonar working parameters.

[0011] Step 3): Calculate the cumulative detection probability of the sonar according to the detection decision model. The detection decision model means that if the target signal is detected M times in N detections, it is considered that the sonar has detected the target.

[0012] Step 4): After the sonar executes the detection task at the current moment, calculate the posterior probability of target presence based on the detection result and the prior probability of target presence before the sonar executes the detection.

[0013] Step 5): Construct the target presence probability transition matrix G, and update the prior probability of target presence at the next moment according to the target presence probability transition matrix and the posterior probability of target presence after the previous detection.

[0014] Step 6): Repeat Step 2) to Step 5) until the dynamic detection efficiency of the sonar within the detection task time is obtained.

[0015] Furthermore, the specific steps for gridding the detection area and initializing the target presence probability are as follows:

[0016] (1) Divide the entire detection area X*Y into N x *N y grids, where N x and N y are the numbers of discrete space grids in the x and y directions respectively. The grid coordinates (x i , y j ) are represented by the following formula:

[0017] N x *Δx = X

[0018] N y *Δy = Y

[0019] N t Δt = T

[0020] x i = iΔx i = 1, 2, …, N x

[0021] y j = jΔy j = 1, 2, …, N y

[0022] t k = kΔt k = 0, 1, 2, …, Nt (1)

[0023] Among them, Δx and Δy determine the grid division interval in the x-y plane, Δt is the discrete unit time increment, T is the total duration of the detection task, and N t is the total number of divisions of the detection task on the time scale; t k is the current time, and the time corresponding to the k-th detection of the detection task;

[0024] (2), set the initial value of the target existence probability P T (x i , y j , 0).

[0025] Furthermore, the specific steps for calculating the instantaneous detection probability of the sonar are as follows:

[0026] During the k-th detection of the sonar at the current time, the detection probability P d (x, y, k) of the underwater at a certain position (x, y) in the detection area is expressed by the calculation formula:

[0027]

[0028] Among them, DT and SNR are respectively the decibel representations of the detection threshold and the signal-to-noise ratio. SNR is calculated by the following formula SNR = SE + DT, where SE is the signal margin. The calculation formula of the multi-static sonar equation is:

[0029] Under the noise masking level: SE = SL - TL1 - TL2 + TS - NL + DI - DT;

[0030] Under the reverberation masking level: SE = SL - TL1 - TL2 + TS - RL + DI - DT;

[0031] Among them, SL is the transmitting sound source level, TL1 and TL2 are respectively the propagation losses from the sound source to the target and from the target to the receiver, TS is the target strength, NL is the noise level, RL is the reverberation level, and DI is the receiving directivity index.

[0032] Furthermore, the specific steps for calculating the cumulative detection probability P cpd (x, y, k) are as follows:

[0033]

[0034] Among them, N is the number of detections, and M is the number of times the target signal is detected.

[0035] Furthermore, the specific steps for calculating the posterior probability of target existence are as follows:

[0036]

[0037] Among them, P T (x, y, k) represents the prior probability of the target's existence at the position (x, y) in the k-th detection at the current moment, where (x, y) is a certain position in the sonar detection area.

[0038] Furthermore, the steps for constructing the target existence probability transition matrix G and updating the prior probability of the target's existence at the next moment are as follows:

[0039] (1) The expression of the target existence probability transition matrix G is:

[0040]

[0041] Among them, m x and m y are drift coefficients, reflecting the average value of the target's movement speed, and 1 / 2σ x 2 and 1 / 2σ y 2 are diffusion coefficients, reflecting the deviation of the target's movement;

[0042] (2) The expression of the prior probability P T (x, y, k + 1) of the target's existence at the next moment is:

[0043]

[0044] Among them, · represents the dot product of the prior probability P T (x, y, k) distribution of the target's existence in the k-th detection at the current moment and the target existence probability transition matrix G.

[0045] The beneficial effects of the present invention are as follows:

[0046] 1. Based on the multi-static sonar equation, the multi-static sonar detection efficiency is analyzed from multiple dimensions including signal margin estimation, signal-to-noise ratio estimation, detection threshold, and sonar detection probability estimation. And according to the sonar detection probability, the calculation method of the cumulative discovery probability and the dynamic efficiency evaluation method are summarized, analyzing the multi-static sonar detection efficiency in the actual detection process from different perspectives.

[0047] 2. Analyze the multi-static detection formation and path under typical detection tasks, and construct multiple different underwater target detection efficiency evaluation indicators from the evaluation of the cumulative discovery probability and the evaluation of the target existence probability to meet different detection requirements.

[0048] 3. For typical detection tasks, the underwater target detection efficiency and dynamic efficiency of a multi-static sonar are calculated and deduced in combination with the working parameters of the multi-static sonar. By constructing different detection efficiency evaluation indexes, the detection efficiency of the multi-static sonar is analyzed from different angles: collaborative detection coverage, collaborative underwater target detection efficiency, and collaborative detection dynamic efficiency, providing a reference basis for the reasonable use of the multi-static sonar by detection users. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings required for use in the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and for those of ordinary skill in the art, other accompanying drawings can be obtained based on these drawings without creative efforts.

[0050] Figure 1 It is a schematic diagram of the implementation process of the present invention.

[0051] Figure 2 It is a schematic diagram of the detection probability simulation of the multi-static sonar 30 minutes after the start of sonar detection.

[0052] Figure 3 It is a schematic diagram of the target existence probability simulation 30 minutes after the start of sonar detection.

[0053] Figure 4 It is a schematic diagram of the detection probability simulation of the multi-static sonar after a period of search task (240 minutes).

[0054] Figure 5 It is a schematic diagram of the target existence probability simulation after a period of search task (240 minutes).

[0055] Figure 6 It is a curve graph showing the change of the regional coverage rate of the multi-static sonar with the search time during dynamic detection. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0056] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] Such as Figure 1As shown in the figure, the present invention provides a method for analyzing the dynamic efficiency of multi-base sonar collaborative detection, which is used to evaluate the detection efficiency of multi-base sonar in the regional target detection scenario. By combining the underwater target detection tactical actions of the surface collaborative platform with the underwater target motion model, a detection efficiency analysis method based on the target presence probability is proposed to obtain a more realistic estimation of the underwater target detection efficiency of the surface platform, and form a dynamic prediction of the sonar's underwater target perception.

[0058] The specific steps are as follows:

[0059] Step 1): Select a detection area, set multi-base sonar nodes in the detection area, grid the detection area, and initialize the target presence probability;

[0060] The specific process of gridding the detection area is to divide the entire detection area X*Y into N x *N y grids, where N x and N y are the number of discrete space grids in the x and y directions respectively. The grid coordinates (x i , y j ) are represented by the following formula:

[0061] N x *Δx = X

[0062] N y *Δy = Y

[0063] N t Δt = T

[0064] x i = iΔx i = 1, 2, …, N x

[0065] y j = jΔy j = 1, 2, …, N y

[0066] t k = kΔt k = 0, 1, 2, …, N t (1)

[0067] where Δx and Δy determine the grid division interval in the x-y plane, Δt is the discrete unit time increment, T is the total duration of the detection task, and N t is the total number of divisions of the detection task on the time scale; t k is the current time, and the detection task corresponds to the time at the kth detection;

[0068] As a preferred technical solution, the initial value of the target presence probability P T (x i , y j,0) is set to 0.5.

[0069] Step 2): At the current moment, according to the real-time ocean environment, combat situation, and sonar working parameters, calculate the sonar instantaneous detection probability P d (x,y,k);

[0070] Specifically, in the k-th detection of the sonar at the current moment, the detection probability P d (x,y,k) of the underwater object at a certain position (x,y) in the detection area is calculated by the following formula:

[0071]

[0072] where DT and SNR are respectively expressed in decibels (dB) of the detection threshold and signal-to-noise ratio. SNR is calculated by the formula SNR = SE + DT, where SE is the signal margin. The calculation formula of the multi-static sonar equation is:

[0073] Under the noise masking level: SE = SL - TL1 - TL2 + TS - NL + DI - DT;

[0074] Under the reverberation masking level: SE = SL - TL1 - TL2 + TS - RL + DI - DT;

[0075] where SL is the transmitting sound source level, TL1 and TL2 are respectively the propagation losses from the sound source to the target and from the target to the receiver, TS is the target strength, NL is the noise level, RL is the reverberation level, and DI is the receiving directivity index.

[0076] Step 3): According to the detection decision model (N - M model), calculate the sonar cumulative detection probability P cpd (x,y,k); The N - M model means that in N detections, if the target signal is detected M times, it is considered that the sonar has detected the target;

[0077] Specifically, the calculation method of the sonar cumulative detection probability P cpd (x,y,k) is as follows

[0078]

[0079] where N is the number of detections and M is the number of times the target signal is detected.

[0080] Step 4): After the sonar executes the detection task at the current moment, according to the detection result and the prior probability P T (x,y,k) of the target existence before the sonar executes the detection, calculate the posterior probability P T|ND (x,y,k);

[0081] Specifically, the calculation formula of the posterior probability of target existence is

[0082]

[0083] Among them, P T (x, y, k) represents the prior probability of the target's existence at the position (x, y) in the k-th detection at the current moment, where (x, y) is a certain position in the sonar detection area.

[0084] Step 5): Construct the target existence probability transition matrix G, and update the prior probability P of the target's existence at the next moment according to the target existence probability transition matrix and the posterior probability of the target's existence after the previous detection T (x, y, k + 1);

[0085] Specifically, the expression of the target existence probability transition matrix G is:

[0086]

[0087] Among them, m x and m y are drift coefficients, reflecting the average value of the target's movement speed, 1 / 2σ x 2 and 1 / 2σ y 2 are diffusion coefficients, reflecting the deviation of the target's movement;

[0088] Furthermore, the expression of the prior probability P of the target's existence at the next moment T (x, y, k + 1) is

[0089]

[0090] Among them, · represents the dot product of the prior probability P of the target's existence T (x, y, k) distribution and the target existence probability transition matrix G in the k-th detection at the current moment.

[0091] Step 6): Repeat Step 2) to Step 5) until the sonar dynamic detection efficiency within the mission time is obtained.

[0092] Figures 2 - 6 It is the simulation result of the regional detection of a three-node multi-static sonar platform, showing how to use the target existence probability to dynamically reflect the perception process of whether there is an underwater target in the detection area. The specific simulation method is that the multi-static sonar searches for targets in the area along a rectangular surrounding path, and the working mode is 2-transmit 3-receive cooperative detection. Specifically, Sonar 1 and Sonar 2 transmit, and Sonar 1 to Sonar 3 receive signals for detection. When the sonar conducts multi-static detection, in order to avoid mutual interference between sonars, a 2-transmit multi-receive cooperative detection method is often adopted.

[0093] At the initial moment of sonar detection, since there is no prior information on the existence of underwater targets, the target existence probability is 0.5 for all cases. At this time, the entire area is covered by red shadows. Figure 3 It is the target existence probability 30 minutes after the start of sonar detection. Obtained from Figure 2 After obtaining the prior information on the existence of underwater targets, some areas within the region change from red shadows to blue shadows. The higher the sonar detection probability of the area, and if the on-site sonar does not report a target, then the target existence probability of the area is smaller, and it appears darker (approaching zero) in the figure. Since the detection task has just been executed, the illuminated area is very small, indicating that most positions in the area are still uncertain whether there are underwater targets.

[0094] Figure 4 It is a schematic diagram of the detection probability simulation of a multi-static sonar after searching for a period of time (240 minutes) on a fixed route. Figure 5 It is a schematic diagram of the target existence probability simulation 240 minutes after the start of sonar detection. It can be seen from Figure 5 that most areas within the region have been detected and illuminated (blue areas) at this time, and no targets appear in this area. However, since the multi-static sonar nodes cannot search areas that have not been searched, most areas within the region are still uncertain whether there are targets.

[0095] Figure 6 It is a curve graph showing the change of the regional coverage rate with the search time during the dynamic detection of a multi-static sonar. Observing the curve, it can be seen that the regional coverage rate shows an upward trend at the initial stage of the search task execution. And as the task time t increases, the curve gradually flattens. Until the later stage of the task, the curve fluctuates up and down around a certain regional coverage rate value.

[0096] The present invention combines the characteristics of multi-static sonar for detecting ocean acoustic environment elements, and constructs a multi-static sonar based on the sound field environment through methods such as sound propagation modeling, reverberation modeling, and background noise modeling. For specific applications, it analyzes the sonar working parameter platform positions, provides a sonar detection performance analysis tool based on environment-platform-sonar parameters for sonar operators, and helps sonar operators improve the collaborative detection ability of multi-static sonars.

[0097] As mentioned above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claimed rights.

Claims

1. A method for analyzing dynamic performance of multi-base sonar cooperative detection, characterized in that: The steps include: Step 1) Select a detection area, set up multi-base sonar nodes in the detection area, grid the detection area, and initialize the target existence probability; Step 2), at the current moment, calculate the sonar instantaneous detection probability based on the real-time ocean environment, combat situation and sonar working parameters; Step 3), according to the detection decision model, calculate the cumulative detection probability of the sonar; the detection decision model means that if there are M detections of target signals in N detections, it is considered that the sonar has found the target; Step 4), after the sonar performs the detection task at the current moment, the posterior probability of the target existence is calculated based on the detection result and the prior probability of the target existence before the sonar performs the detection; Step 5) Construct the target existence probability transfer matrix G and update the target existence prior probability at the next moment; Step 6), repeat step 2) to step 5) until the sonar dynamic detection efficiency within the detection mission time is obtained; The calculation of the sonar cumulative detection probability P cpd (x,y,k), the specific steps are: Where N is the number of detections, M is the number of times the target signal is found; P d (x, y, k) is the probability of the sonar detecting an underwater object at a certain position (x, y) in the detection area in the kth detection at the current moment; The calculation target has a posterior probability, and the specific steps are: Among them, P T (x, y, k) represents the prior probability of the existence of a target at (x, y) in the kth detection at the current moment, and (x, y) is a certain position in the sonar detection area.

2. The method for dynamic performance analysis of multi-base sonar cooperative detection according to claim 1 is characterized in that: The detection area is gridded and the target existence probability is initialized. The specific steps are: (1) Divide the entire detection area X*Y into N x *N y grids, N x and N y are the number of discrete spatial grids in the x and y directions, respectively, and the grid coordinates (x i ,y j ) is expressed as follows: N x *Δx=X N y *Δy=Y N t Δt=T x i =iΔx i=1,2,…,N x y j =jΔy j=1,2,…,N y t k =kΔt k=0,1,2,…,N t (1) Among them, Δx and Δy determine the grid division interval in the xy plane, Δt is the discrete unit time increment, T is the total duration of the detection task, and N t is the total number of detection tasks divided on the time scale; t k is the time corresponding to the kth detection of the detection task at the current moment; (2) Set the initial value P of the target existence probability T (x i ,y j ,0).

3. The method for dynamic performance analysis of multi-base sonar cooperative detection according to claim 2 is characterized in that: The specific steps of calculating the sonar instantaneous detection probability are as follows: The probability P of the sonar detecting an underwater object at a certain position (x, y) in the detection area during the kth detection at the current time is d The calculation formula of (x,y,k) is expressed as: Among them, DT and SNR are the decibels of the detection threshold and signal-to-noise ratio respectively. SNR is calculated by the following formula: SNR = SE + DT, SE is the signal margin, and the calculation formula of the multi-base sonar equation is: At the noise masking level: SE = SL-TL1-TL2+TS-NL+DI-DT; At the reverberation masking level: SE = SL-TL1-TL2+TS-RL+DI-DT; Among them, SL is the transmitting sound source level, TL1 and TL2 are the propagation losses from the sound source to the target and from the target to the receiver respectively, TS is the target strength, NL is the noise level, RL is the reverberation level, and DI is the receiving directivity index.

4. The method for dynamic performance analysis of multi-base sonar cooperative detection according to claim 3 is characterized in that: The target existence probability transfer matrix G is constructed to update the prior probability of the target existence at the next moment. The specific steps are: (1) The expression of target existence probability transfer matrix G is: Among them, m x and m y is the drift coefficient, which reflects the mean speed of the target, 1 / 2σ x 2 and 1 / 2σ y 2 is the diffusion coefficient, which reflects the deviation of the target motion; (2) The prior probability P of the target existing at the next moment T The expression for (x,y,k+1) is: Where · represents the prior probability P of the target existing in the kth detection at the current moment T The dot product of the (x,y,k) distribution and the target existence probability transfer matrix G.

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