Multi-base sonar cooperative detection dynamic performance analysis method

Abstract

The invention provides a multi-base sonar cooperative detection dynamic efficiency analysis method, which comprises the following steps of: 1) selecting a detection area, setting multi-base sonar nodes in the detection area, and gridding the detection area; 2) calculating the instantaneous sonar detection probability at the current moment; step 3), calculating a sonar cumulative discovery probability; 4) after the sonar executes the detection task at the current moment, calculating the target existence posterior probability by using the target existence prior probability before the sonar executes the detection; 5) constructing a target existence probability transfer matrix G, and updating the target existence prior probability at the next moment; and 6) repeating the step 2) to the step 5) until the sonar dynamic detection efficiency within the detection task time is obtained. According to the method, the multi-base sonar detection efficiency is analyzed from multiple dimensions, a cumulative discovery probability calculation method and a dynamic efficiency evaluation method are summarized according to the sonar detection probability, and the multi-base sonar detection efficiency in the actual detection process is analyzed from different angles.

Description

Technical Field

[0001] The invention relates to the technical field of sonar detection, and mainly relates to a dynamic effectiveness analysis method for multi-base sonar cooperative detection. Background Art

[0002] The problem of underwater target detection is a key issue that restricts the improvement of marine area warning capabilities. In shallow waters, due to high environmental noise and the increasing "quietness" of underwater targets, the passive detection range is getting closer and closer, and the use of active detection of underwater targets has become a new hotspot. However, in complex shallow sea environments, active sonar will be severely interfered by reverberation and false targets, and its detection capabilities will also be severely limited. Multi-base sonar has the advantages of concealment, large detection range, and high detection and identification probability. It is one of the effective methods to improve shallow sea detection capabilities.

[0003] In the domestic research on multi-base sonar, simulations and calculations have been carried out on multi-base sonar equations and performance analysis, multi-base sonar system composition schemes, multi-base reverberation calculations and target strength. The relationship between multi-base sonar positioning errors and structures and the optimal receiver structure have been studied. Some experiments have also been conducted to preliminarily verify the feasibility of multi-base detection.

[0004] The multi-base collaborative detection effectiveness analysis and deduction method is the premise and key to the efficient use of detection platforms to implement underwater moving target detection. Due to the complexity and variability of the marine environment and the strong dependence of sonar detection performance on the marine environment, multi-base collaborative detection only relies 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 effectiveness. Detection users lack understanding of the performance of multi-base collaborative detection, which is mainly manifested in:

[0005] First, in a complex and changeable ocean environment, it is difficult for users to accurately estimate the detection performance of sonar, resulting in missed situations or inefficiency. Sonar operators find it difficult to select appropriate sonar operating parameters, resulting in the failure to fully utilize the detection performance of multi-base sonar.

[0006] Second, the means of evaluating the effectiveness of multi-base collaborative detection is not perfect in the probability assessment model for underwater moving target detection. The results of multi-base collaborative detection are highly random and cannot achieve a steady improvement in the ability to detect underwater moving targets. Summary of the invention

[0007] The present invention aims at how to evaluate the detection efficiency of multi-base sonar in a regional target detection scenario, and provides a multi-base sonar collaborative detection dynamic efficiency analysis method.

[0008] The object of the present invention is achieved through the following technical solution: A method for analyzing the dynamic effectiveness of multi-base sonar cooperative detection, comprising the following steps: Step 1), select the 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) 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 found M times 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 results 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 according to the target existence probability transfer matrix and the target existence posterior probability after the last detection; Step 6) Repeat steps 2) to 5) until the sonar dynamic detection efficiency within the detection mission time is obtained.

[0009] Furthermore, the detection area is gridded and the target existence probability is initialized, and the specific steps are: (1) Divide the entire detection area X*Y into A grid, and They are and The number of discrete spatial grids in the direction, the grid coordinates ( , ) is expressed as follows: ; ; ; ; ; (1) in, and Sure The grid division interval in the plane, is the discrete unit time increment, T is the total duration of the detection task, The total number of detection tasks divided in the time scale; is the current moment, and the detection task is The time corresponding to the detection; (2) Set the initial value of the target existence probability .

[0010] Furthermore, the specific steps of calculating the sonar instantaneous detection probability are as follows: In the kth detection at the current moment, the sonar detects a certain position in the detection area Probability of underwater detection The calculation formula is expressed as: (2) Among them, DT and SNR are the decibels of detection threshold and signal-to-noise ratio respectively. SNR is calculated by the following formula: , SE is the signal margin, and the calculation formula of the multi-base sonar equation is: At the noise masking level: ; At reverberation masking level: ; Where SL is the emission source level, , are 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, DI is the receiving directivity index, and DT is the detection threshold.

[0011] Furthermore, the calculation of the sonar cumulative detection probability , the specific steps are: (3) in, is the number of detections, The number of times the target signal is found.

[0012] Furthermore, the calculation target has a posterior probability, and the specific steps are: (4) in, Indicates that in the kth detection at the current moment, There is a priori probability of the target, A location in the sonar detection area.

[0013] Furthermore, the construction target has a probability transfer matrix , update the prior probability of the target existence at the next moment, the specific steps are: (1) Target existence probability transfer matrix The expression is: (5) in, and is the drift coefficient, which reflects the mean speed of the target. and is the diffusion coefficient, which reflects the deviation of the target motion; (2) The prior probability of the target existing at the next moment The expression is: (6) Where, • represents the probability of the target existing in the kth detection at the current moment. Distribution and target existence probability transfer matrix The dot product of .

[0014] The beneficial effects of the present invention are: 1. Based on the multi-base sonar equation, the multi-base sonar detection effectiveness is analyzed from multiple dimensions including signal margin estimation, signal-to-noise ratio estimation, detection threshold and sonar detection probability estimation. The cumulative discovery probability calculation method and dynamic effectiveness evaluation method are summarized according to the sonar detection probability. The multi-base sonar detection effectiveness in the actual detection process is analyzed from different perspectives.

[0015] 2. The multi-base detection formation and path under typical detection tasks are analyzed, and multiple different underwater target detection effectiveness evaluation indicators are constructed from the cumulative discovery probability evaluation and target existence probability evaluation to meet different detection needs.

[0016] 3. For typical detection tasks, the underwater target detection efficiency and dynamic efficiency of multi-base sonar are calculated and derived in combination with the working parameters of multi-base sonar. By constructing different detection efficiency evaluation indicators, the detection efficiency of multi-base sonar is analyzed from different angles: collaborative detection coverage, collaborative underwater target detection efficiency and collaborative detection dynamic efficiency, providing a reference for detection users to use multi-base sonar rationally. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art or ordinary technicians, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of the implementation process of the present invention.

[0019] Figure 2 This is a schematic diagram of the detection probability simulation of multi-base sonar 30 minutes after the start of sonar detection.

[0020] Figure 3 This is a simulation diagram of the target existence probability 30 minutes after the start of sonar detection.

[0021] Figure 4 Schematic diagram of the detection probability simulation of multi-base sonar after a period of search mission (240 minutes).

[0022] Figure 5 Schematic diagram of the simulation of target existence probability after a period of search mission (240 minutes).

[0023] Figure 6 This is a graph showing how area coverage changes with search time during multi-base sonar dynamic detection. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of the present invention.

[0025] like Figure 1 As shown, the present invention provides a multi-base sonar cooperative detection dynamic effectiveness analysis method, which is used to evaluate the detection effectiveness of multi-base sonar in the regional target detection scenario. The underwater target detection tactical action of the surface cooperative platform is combined with the underwater target motion model, and a detection effectiveness analysis method based on the target existence probability is proposed to obtain a surface platform underwater target detection effectiveness estimation that is more in line with actual conditions, and form a dynamic forecast of sonar underwater target perception.

[0026] The specific steps are as follows: Step 1), select the detection area, set up multi-base sonar nodes in the detection area, grid the detection area, and initialize the target existence probability; The specific process of gridding the detection area is to divide the entire detection area X*Y into A grid, and They are and The number of discrete spatial grids in the direction, the grid coordinates ( , ) is expressed as follows:

[0027]

[0028]

[0029]

[0030]

[0031] (1) in, and Sure The grid division interval in the plane, is the discrete unit time increment, T is the total duration of the detection task, The total number of detection tasks divided in the time scale; is the current moment, and the detection task is The time corresponding to the detection; As a preferred technical solution, the target existence probability value initial value Set to 0.5.

[0032] 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 ; Specifically, in the kth detection at the current moment, the sonar detects a certain position in the detection area. Probability of underwater detection The calculation formula is expressed as: (2) Among them, DT and SNR are the detection threshold and signal-to-noise ratio expressed in decibels (dB), respectively. SNR is calculated by the following formula: , SE is the signal margin, and the calculation formula of the multi-base sonar equation is: At the noise masking level: ; At reverberation masking level: ; Where SL is the emission source level, , are 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, DI is the receiving directivity index, and DT is the detection threshold.

[0033] Step 3), according to the detection decision model ( model), calculate the cumulative probability of sonar discovery ; The model refers to In this detection, if there is If the target signal is detected for the first time, it is considered that the sonar has detected the target; Specifically, the sonar cumulative detection probability The calculation method is as follows (3) in, is the number of detections, The number of times the target signal is found.

[0034] Step 4) After the sonar performs the detection task at the current moment, the target existence prior probability is calculated based on the detection results and the sonar detection result. , calculate the posterior probability of the target existence ; Specifically, the formula for calculating the posterior probability of target existence is: (4) in, Indicates that in the kth detection at the current moment, There is a priori probability of the target, A location in the sonar detection area.

[0035] Step 5) Construct the target existence probability transfer matrix , according to the target existence probability transfer matrix and the posterior probability of the target existence after the last detection, update the prior probability of the target existence at the next moment ; Specifically, the target existence probability transfer matrix The expression is: (5) in, and is the drift coefficient, which reflects the mean speed of the target. and is the diffusion coefficient, which reflects the deviation of the target motion; Furthermore, there is a prior probability that the target exists at the next moment The expression is (6) Where, • represents the probability of the target existing in the kth detection at the current moment. Distribution and target existence probability transfer matrix The dot product of .

[0036] Step 6) Repeat steps 2) to 5) until the sonar dynamic detection performance within the mission time is obtained.

[0037] Figure 2-Figure 6 The simulation results of regional detection of a three-node multi-base sonar platform illustrate how to use the target existence probability to dynamically reflect the perception process of whether there are underwater targets in the detection area. The simulation method is that the multi-base sonar searches for targets in the area according to a rectangular surround path, and the working mode is 2-transmit 3-receive collaborative detection, specifically sonar 1 and sonar 2 transmit, and sonar 1 to sonar 3 receive signals for detection. In order to avoid mutual interference between sonars when performing multi-base detection, the 2-transmit multi-receive collaborative detection method is often used.

[0038] At the initial moment of sonar detection, since there is no prior information about the existence of underwater targets, the probability of target existence is 0.5, and the entire area is covered by red shadows. Figure 3 is the probability of target existence 30 minutes after the start of sonar detection, given by Figure 2 After obtaining the prior information about the existence of underwater targets, some areas in the region change from red to blue. The higher the sonar detection probability of the region, and the less the target is reported by the on-site sonar, the lower the probability of the target existing in the region, and the darker the image (approaching zero). Since the detection mission has just been carried out, the illuminated area is very small, indicating that most of the area is still uncertain whether there is an underwater target.

[0039] Figure 4 This is a simulation diagram of the detection probability of multi-base sonar after a period of time (240 minutes) of multi-base sonar search missions on a fixed route. Figure 5 This is a simulation diagram of the target existence probability 240 minutes after the start of sonar detection. Figure 5 It can be seen that most of the area has been detected and illuminated (blue area), and no target appears in the area. However, since the multi-base sonar node cannot search areas that have not been searched, there are still most areas in the area where it is uncertain whether there are targets.

[0040] Figure 6 This is a curve of the area coverage rate changing with the search time during multi-base sonar dynamic detection. From the curve, we can see that the area coverage rate shows an upward trend in the early stage of the search mission, and as the mission time t increases, the curve gradually flattens until the end of the mission, when the curve fluctuates around a certain area coverage rate value.

[0041] The present invention combines the characteristics of multi-base sonar detection of ocean acoustic environment elements, and constructs a multi-base sonar based on the sound field environment through sound propagation modeling, reverberation modeling, background noise modeling, etc. According to specific applications, the sonar working parameters, platform positions are analyzed, and a sonar detection performance analysis tool based on environment-platform-sonar parameters is provided for sonar operators to help sonar operators improve the multi-base sonar collaborative detection capabilities.

[0042] The above is only a specific embodiment 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 a person skilled in the art within the scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for analyzing dynamic performance of multi-base sonar cooperative detection, characterized in that: The steps include: Step 1), select the 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) Calculate the cumulative detection probability of sonar according to the detection decision model; the detection decision model refers to In this detection, if there is If the target signal is detected for the first time, it is considered that the sonar has detected 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 results and the prior probability of the target existence before the sonar performs the detection; Step 5) Construct the target existence probability transfer matrix , update the prior probability of the target existence at the next moment; Step 6) Repeat steps 2) to 5) until the sonar dynamic detection efficiency within the detection mission time is obtained.

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 A grid, and They are and The number of discrete spatial grids in the direction, the grid coordinates ( , ) is expressed as follows: ； ； ； ； ； （1） in, and Sure The grid division interval in the plane, is the discrete unit time increment, T is the total duration of the detection task, The total number of detection tasks divided in the time scale; is the current moment, the detection task is The time corresponding to the detection; (2) Set the initial value of the target existence probability .

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: In the kth detection at the current moment, the sonar detects a certain position in the detection area Probability of underwater detection The calculation formula is expressed as: （2） Among them, DT and SNR are the decibels of detection threshold and signal-to-noise ratio respectively. SNR is calculated by the following formula: , SE is the signal margin, and the calculation formula of the multi-base sonar equation is: At the noise masking level: ; At reverberation masking level: ; Where SL is the emission source level, , are 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, DI is the receiving directivity index, and DT is the detection threshold.

4. The method for dynamic performance analysis of multi-base sonar cooperative detection according to claim 3 is characterized in that: The calculation of sonar cumulative detection probability , the specific steps are: （3） in, is the number of detections, The number of times the target signal is found.

5. The method for dynamic performance analysis of multi-base sonar cooperative detection according to claim 4 is characterized in that: The calculation target has a posterior probability, and the specific steps are: （4） in, Indicates that in the kth detection at the current moment, The prior probability of the target is A location in the sonar detection area.

6. The method for dynamic performance analysis of multi-base sonar cooperative detection according to claim 5, characterized in that: The constructed target has a probability transfer matrix , update the prior probability of the target existence at the next moment, the specific steps are: (1) Target existence probability transfer matrix The expression is: （5） in, and is the drift coefficient, which reflects the mean speed of the target. and is the diffusion coefficient, which reflects the deviation of the target motion; (2) The prior probability of the target existing at the next moment The expression is: （6） Where, • represents the probability of the target existing in the kth detection at the current moment. Distribution and target existence probability transfer matrix The dot product of .

Images