Underwater passive detection-oriented mutual detection evaluation method and device

Abstract

The invention relates to the technical field of underwater passive detection, in particular to a mutual detection evaluation method and device for underwater passive detection. The method comprises the following steps: according to target detectable characteristic parameters and target detection performance of two targets to be detected and environmental noise distribution, calculating signal margin parameters of a target I and a target II before opposite side detection; calculating a first conditional probability and a second conditional probability that the target I and the target II detect the opposite side according to the signal margin parameter and an environmental noise probability density function before the two to-be-detected targets are put; and calculating a mutual probability factor between the target I and the target II according to the first conditional probability and the second conditional probability. According to the method, the target I and the target II are quantified under the same dimension, and the process is regarded as a conditional probability, so that the purpose of quantifying the mutual search capability of the target I and the target II at different spatial positions is achieved, and scientific and effective quantitative evaluation balance is provided for the mutual search capability of the two underwater targets.

Description

Technical Field

[0001] The present application relates to the technical field of underwater passive detection, and in particular to a mutual detection evaluation method and device for underwater passive detection. Background Art

[0002] The marine hydrological environment is complex, and the target data detected by the sonar equipment carried by the underwater platform often contains a large number of interfering targets, making the target difficult to identify. In addition, active detection is easy to expose its own position. In an environment with "concealment" requirements, passive detection is often used. Underwater passive detection technology refers to the use of sonar to passively receive the radiation noise generated by underwater targets such as ships and the signals emitted by hydroacoustic equipment to determine the direction and distance of the target. Since the passive sonar itself does not emit signals, the target will not be aware of the existence of the sonar and its intentions. Therefore, in underwater passive detection, it is necessary not only to measure one's own detection capabilities, but also to hide one's own existence as much as possible, that is, to measure the ability of underwater targets to search for each other.

[0003] The mutual search capability of two underwater targets is related to both the target detection capability and the target characteristics of the target being searched. However, in the relevant technology, the evaluation criteria for target detection capability and target characteristics are independent of each other, and there is a lack of a criterion for quantitatively evaluating the two in the same dimension, which makes it impossible to quantitatively evaluate the mutual search capability between targets. Summary of the invention

[0004] Regarding the relevant technologies, the evaluation criteria for target detection capability and target characteristics are independent of each other, and there is a lack of criteria for quantitatively evaluating the two in the same dimension, which makes it impossible to quantitatively evaluate the mutual search capability between targets.

[0005] In a first aspect, an embodiment of the present application provides a mutual detectability evaluation method for underwater passive detection, the mutual detectability evaluation method comprising: According to the target detectability characteristic parameters and target detection performance of the two targets to be detected and the distribution of environmental noise, the signal margin parameters of target one and target two before detecting each other are calculated; According to the signal margin parameter and the probability density function of the environmental noise before the two targets are released, the first conditional probability and the second conditional probability that the target one and the target two detect each other are calculated; The mutual exploration factor between target one and target two is calculated according to the first conditional probability and the second conditional probability.

[0006] In combination with the first aspect, in one implementation, calculating the mutual exploration factor between the first target and the second target according to the first conditional probability and the second conditional probability includes: The mutual exploration factor Q between target one and target two is calculated according to the formula:

[0007] In the formula, is the first conditional probability, is the second conditional probability.

[0008] Combined with the first aspect, in one embodiment, calculating the mutual detection factor between target one and target two according to the first conditional probability and the second conditional probability further includes: Taking target one as the center, placing target two at different positions in the confrontation area; Calculating the detection probability between target two and target one when target two is in different areas, and drawing a detection probability graph for both sides.

[0009] Combined with the first aspect, in one embodiment, calculating the mutual detection factor between target one and target two according to the first conditional probability and the second conditional probability includes: Taking target one as the center, placing target two at different positions in the confrontation area; Calculating the mutual detection factor between target two and target one when target two is in different areas, and drawing a mutual detection factor graph according to the mutual detection factors of both sides.

[0010] Combined with the first aspect, in one embodiment, according to the signal margin parameter and the environmental noise probability density function before placing two targets to be measured, it includes: Obtaining the environmental noise level, the radiated noise level of the target to be measured, the propagation loss between two targets to be measured, and the passive sonar array gain parameter of the target to be measured; Calculating the signal margin parameter of target one and target two before detecting each other according to the environmental noise level, the radiated noise level of the target to be measured, the propagation loss between two targets to be measured, and the passive sonar array gain parameter of the target to be measured.

[0011] Combined with the first aspect, in one embodiment, calculating the signal margin parameter of target one and target two before detecting each other according to the environmental noise level, the radiated noise level of the target to be measured, the propagation loss between two targets to be measured, and the passive sonar array gain parameter of the target to be measured includes: calculating the first signal margin parameter of target one according to the formula and the second signal margin parameter of target two :

[0012]

[0013] In the formula, and are respectively the radiated noise levels of target one and target two, is the propagation loss from target two to target one, The propagation loss from target one to target two is the environmental noise level and are the passive sonar array gains of target one and target two respectively.

[0014] Combined with the first aspect, in one embodiment, the obtaining of the passive sonar array gain parameter of the target to be measured includes: Obtaining the number of elements of the first passive sonar array of target one and the number of elements of the second passive sonar array of target two; Calculating the first passive sonar array gain of target one and the second passive sonar array gain of target two :

[0015]

[0016] wherein is the number of elements of the first passive sonar array is the number of elements of the second passive sonar array.

[0017] Combined with the first aspect, in one embodiment, the obtaining of the environmental noise level includes: determining the environmental noise level and the environmental noise probability density function according to the historical data of the detection environment.

[0018] Combined with the first aspect, in one embodiment, the calculating of the first conditional probability and the second conditional probability that target one and target two detect each other according to the environmental noise probability density function and the signal margin parameter when the two targets to be measured do not exist includes: When the environmental noise probability density function conforms to Gaussian white noise of normal distribution, calculating the first conditional probability of target one according to the formula and the second conditional probability of target two :

[0019]

[0020] wherein is the environmental noise standard deviation is that the signal detected by target one contains the radiation noise event of target two is that the signal detected by target two contains the radiation noise event of target one is the detection threshold.

[0021] In a second aspect, an embodiment of the present application provides a mutual detection evaluation device for underwater passive detection, and the mutual detection factor calculation device includes: A signal margin calculation unit, which is used to calculate the signal margin parameters of Target 1 and Target 2 before detecting each other according to the target detectability characteristic parameters, target detection performance, and environmental noise distribution of two targets to be detected; A probability calculation unit, which is used to calculate the first conditional probability and the second conditional probability of Target 1 and Target 2 detecting each other according to the environmental noise probability density function and signal margin parameters when the two targets to be detected do not exist; An evaluation unit, which is used to calculate the mutual detection factor between Target 1 and Target 2 according to the first conditional probability and the second conditional probability.

[0022] The beneficial effects brought by the technical solution provided by the embodiment of the present application include: The present application simultaneously considers the target characteristics and detection capabilities of Target 1 and Target 2, quantifies them in the same dimension, regards this process as a conditional probability, and gives a calculation method for the mutual detection factor between the two targets, so as to achieve the purpose of quantifying the mutual search capabilities of Target 1 and Target 2 at different spatial positions, and provides a scientific and effective quantitative evaluation criterion for the mutual search capabilities of two underwater targets. Description of the Drawings

[0023] Figure 1 It is a schematic flow chart of the mutual detection evaluation method of the present application; Figure 2 It is a schematic flow chart of the mutual detection evaluation method in a specific embodiment of the present application; Figure 3 It is a detection probability diagram of Target 1 for Target 2 in the embodiment of the present application; Figure 4 It is a detection probability diagram of Target 2 for Target 1 in the embodiment of the present application; Figure 5 It is a mutual detection factor diagram of Target 1 for Target 2 in the embodiment of the present application; Figure 6 It is a schematic hardware structure diagram of the mutual detection evaluation device involved in the embodiment of the present application. Detailed Embodiments

[0024] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0025] Regarding the relevant technologies, the evaluation criteria for target detection capability and target characteristics are independent of each other, and there is a lack of criteria for quantitatively evaluating the two in the same dimension, which makes it impossible to quantitatively evaluate the mutual search capability between targets.

[0026] First, as Figure 1 As shown, the embodiment of the present application provides a mutual detectability evaluation method for underwater passive detection, and the mutual detectability evaluation method includes: Step S1, calculating the signal margin parameters of target 1 and target 2 before detecting each other according to the target detectability characteristic parameters and target detection performance of two targets to be detected and the environmental noise distribution.

[0027] Specifically, the environmental noise level, the radiation noise level of the target to be measured, the propagation loss between the two targets to be measured, and the passive sonar array gain parameters of the target to be measured can be obtained. Then, the signal margin parameters of target one and target two before detecting each other are calculated based on the environmental noise level, the radiation noise level of the target to be measured, the propagation loss between the two targets to be measured, and the passive sonar array gain parameters of the target to be measured.

[0028] Furthermore, if Figure 2 As shown, in some specific embodiments, the above step S1 includes: Step S1a: Obtain environmental noise distribution.

[0029] Specifically, the environmental noise level is determined based on the historical data of the hidden environment. And the ambient noise probability density function P.

[0030] In some optional embodiments, taking Gaussian white noise with normal distribution as an example, for events without target signals , the probability density function of the signal received by the sonar is:

[0031] It is understood that the signal probability density function is used for subsequent calculation of the detection probability.

[0032] Step S1b, obtaining target detectable characteristic parameters.

[0033] Specifically, input relevant parameters according to the target characteristics, such as the target radiated noise level and , subscript Indicates goal one, Indicates goal two.

[0034] Step S1c, obtaining passive detection performance parameters, and calculating passive sonar array gain parameters of the target to be detected.

[0035] Specifically, obtain the number of the first passive sonar array elements of target one and the number of the second passive sonar array elements of target two; calculate the gain of the first passive sonar array of target one according to the number of the first passive sonar array elements and the number of the second passive sonar array elements and the gain of the second passive sonar array of target two :

[0036]

[0037] In the formula, is the number of the first passive sonar array elements, is the number of the second passive sonar array elements.

[0038] Step S1d: Calculate the signal margin parameters of target one and target two before detecting each other according to the ambient noise level, the radiated noise level of the target to be measured, the propagation loss between the two targets to be measured, and the passive sonar array gain parameters of the target to be measured.

[0039] Specifically, calculate the first signal margin parameter of target one according to the formula and the second signal margin parameter of target two :

[0040]

[0041] In the formula, and are the radiated noise levels of target one and target two respectively, is the propagation loss from target two to target one, is the propagation loss from target one to target two, is the ambient noise level, and are the passive sonar array gains of target one and target two respectively.

[0042] Step S2: Calculate the first conditional probability and the second conditional probability that target one and target two detect each other according to the signal margin parameters and the ambient noise probability density functions of the two targets to be measured before being put into use.

[0043] It should be noted that the ambient noise probability density function needs to be determined according to the noise environment.

[0044] In some specific embodiments, when the ambient noise probability density function conforms to Gaussian white noise with a normal distribution, calculate the first conditional probability that target one detects target two according to the formula and the second conditional probability that target two detects target one :

[0045]

[0046] In the formula, is the standard deviation of ambient noise, The signal detected for target 1 contains the radiation noise event of target 2. The signal detected for target 2 contains the radiation noise event of target 1. is the detection threshold.

[0047] Step S3: Calculate the mutual exploration factor between target 1 and target 2 according to the first conditional probability and the second conditional probability.

[0048] It should be noted that, under the premise that target 1 and target 2 are mutually detectable, the detection probability of target 1 to target 2 is , divided by the detection probability of target 2 to target 1 , we can get the mutual exploration factor between target one and target two :

[0049] In the formula, is the first conditional probability, is the second conditional probability. It should be noted that the present application achieves the purpose of quantifying the mutual search capability of target one and target two by obtaining the mutual exploration factor Q of target one to target two at the current empty position.

[0050] In some preferred embodiments, Figure 3 , Figure 4 and Figure 5 As shown, in order to clearly show the mutual detectability between the targets to be tested, the mutual detection probability graph and the mutual detectability factor graph can be drawn.

[0051] Specifically, with target one as the center, target two is placed at a point in the environment, target two is traversed through the confrontation area, and the mutual exploration evaluation method mentioned above is used to calculate the detection probability and mutual exploration factor of target two in different areas. , thus obtaining the detection probability graph and mutual exploration factor graph of both parties (such as Figure 2 , 3 , 4, where the horizontal axis represents the horizontal distance and the vertical axis represents the vertical depth). In this embodiment, the region where the detection probability of both parties is less than a certain value is regarded as a region where mutual detection cannot be formed, and this region is marked in black.

[0052] In a second aspect, the present application provides a mutual detectability evaluation device for underwater passive detection, wherein the mutual detectability evaluation includes: a signal margin calculation unit, a probability calculation unit and an evaluation unit; wherein, A signal margin calculation unit, which is configured to calculate the signal margin parameters of Target 1 and Target 2 before detecting each other according to the target detectable characteristic parameters, target detection performance of two targets to be detected, and environmental noise distribution; a probability calculation unit, which is configured to calculate the first conditional probability and the second conditional probability of Target 1 and Target 2 detecting each other according to the environmental noise probability density function and signal margin parameters when the two targets to be detected do not exist; an evaluation unit, which is configured to calculate the mutual detection factor between Target 1 and Target 2 according to the first conditional probability and the second conditional probability.

[0053] Wherein, the function implementation of each module in the above mutual detection evaluation device corresponds to each step in the embodiment of the above mutual detection evaluation device, and its function and implementation process will not be described in detail here.

[0054] In a third aspect, an embodiment of the present application provides a mutual detection evaluation device, and the mutual detection evaluation device may be a device with data processing functions such as a personal computer (PC), a laptop computer, a server, etc.

[0055] Referring to Figure 6 , Figure 6 is a schematic hardware structure diagram of the mutual detection evaluation device involved in the solution of the embodiment of the present application. In the embodiment of the present application, the mutual detection evaluation device may include a processor, a memory, a communication interface, and a communication bus.

[0056] Among them, the communication bus can be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0057] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces, etc., which are used to implement the interconnection of components inside the mutual detection evaluation device, and interfaces used to implement the interconnection of the mutual detection evaluation device with other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display (Display), a keyboard (Keyboard), etc.

[0058] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical memory, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0059] The processor can be a general-purpose processor, which can call the mutual detection evaluation program stored in the memory and execute the mutual detection evaluation method provided by the embodiments of the present application. For example, the general-purpose processor can be a central processing unit (CPU). Among them, the method executed when the mutual detection evaluation program is called can refer to the various embodiments of the mutual detection evaluation method of the present application, which will not be elaborated here.

[0060] Those skilled in the art can understand that Figure 6 the hardware structure shown in does not constitute a limitation to the present application, and may include more or fewer components than shown, or combine some components, or have different component arrangements.

[0061] Fourthly, the embodiments of the present application also provide a computer-readable storage medium.

[0062] The mutual detection evaluation program is stored on the computer-readable storage medium of the present application. When the mutual detection evaluation program is executed by a processor, the steps of the mutual detection evaluation method as described above are implemented.

[0063] Among them, the method implemented when the mutual detection evaluation program is executed can refer to the various embodiments of the mutual detection evaluation method of the present application, which will not be elaborated here.

[0064] To sum up, the present application simultaneously considers the target characteristics and detection capabilities of Target 1 and Target 2, quantifies them in the same dimension, and regards this process as a conditional probability, and gives a calculation method for the mutual detection factor between the two targets, so as to achieve the purpose of quantifying the mutual search capabilities of Target 1 and Target 2 at different spatial positions, and provides a scientific and effective quantitative evaluation criterion for the mutual search capabilities of two underwater targets.

[0065] It should be noted that the serial numbers of the above embodiments of the present application are only for description and do not represent the superiority or inferiority of the embodiments.

[0066] The terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices. The descriptions of terms such as "Target 1", "Target 2" and "Target 3" are used to distinguish different objects, etc. They do not represent a sequence, nor do they limit that "Target 1", "Target 2" and "Target 3" are different types.

[0067] In the description of the embodiments of this application, words such as "exemplary", "for example", or "for illustration" are used to indicate examples, illustrations, or explanations. Any embodiment or design solution described as "exemplary", "for example", or "for illustration" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary", "for example", or "for illustration" is intended to present related concepts in a specific manner.

[0068] In the description of the embodiments of this application, unless otherwise specified, " / " means "or". For example, A / B can mean A or B; "and / or" in the text is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "a plurality of" means two or more than two.

[0069] In some processes described in the embodiments of this application, there are multiple operations or steps that appear in a specific order. However, it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of this application or may be executed in parallel. The serial numbers of the operations are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in order or in parallel, and these operations or steps may be combined.

[0070] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium as described above (such as ROM / RAM, magnetic disk, optical disc), and includes several instructions to enable a terminal device to execute the methods described in the various embodiments of this application.

[0071] The above are only the preferred embodiments of this application, and do not limit the patent scope of this application. Any equivalent structural or equivalent process transformation made by using the specification and drawings of this application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of this application.

Claims

1. A mutual detection evaluation method for underwater passive detection, characterized in that: The mutual exploration evaluation method comprises: According to the target detectability characteristic parameters and target detection performance of the two targets to be detected and the distribution of environmental noise, the signal margin parameters of target one and target two before detecting each other are calculated; According to the signal margin parameter and the probability density function of the environmental noise before the two targets are released, the first conditional probability and the second conditional probability that the target one and the target two detect each other are calculated; The mutual exploration factor between target one and target two is calculated according to the first conditional probability and the second conditional probability.

2. The mutual detection evaluation method for underwater passive detection according to claim 1, characterized in that: The calculating the mutual exploration factor between the first target and the second target according to the first conditional probability and the second conditional probability includes: The mutual exploration factor Q between target one and target two is calculated according to the formula: In the formula, is the first conditional probability, is the second conditional probability.

3. The mutual detection evaluation method for underwater passive detection as claimed in claim 2, characterized in that: The calculating of the mutual exploration factor between the first target and the second target according to the first conditional probability and the second conditional probability also includes: With target one as the center, target two is placed at different locations in the confrontation area; Calculate the detection probability of target 2 with target 1 when it is in different areas, and draw a detection probability graph of both parties.

4. The mutual detection evaluation method for underwater passive detection as claimed in claim 2, characterized in that: The calculating the mutual exploration factor between the first target and the second target according to the first conditional probability and the second conditional probability includes: With target one as the center, target two is placed at different locations in the confrontation area; Calculate the mutual exploration factor between target 2 and target 1 when they are in different areas, and draw a mutual exploration factor graph based on the mutual exploration factors of both parties.

5. The mutual detection evaluation method for underwater passive detection according to claim 1, characterized in that: The method according to the signal margin parameter and the environmental noise probability density function before the two targets to be tested are released includes: Obtain the environmental noise level, the radiation noise level of the target to be measured, the propagation loss between two targets to be measured, and the passive sonar array gain parameters of the target to be measured; The signal margin parameters of target one and target two before detecting each other are calculated according to the environmental noise level, the radiation noise level of the target to be measured, the propagation loss between the two targets to be measured and the passive sonar array gain parameters of the targets to be measured.

6. The mutual detection evaluation method for underwater passive detection as claimed in claim 5, characterized in that: The method of calculating the signal margin parameters of target one and target two before detecting each other based on the environmental noise level, the radiation noise level of the target to be measured, the propagation loss between the two targets to be measured, and the passive sonar array gain parameters of the target to be measured comprises: calculating the first signal margin parameter of target one according to the formula and the second signal margin parameter of target 2 : In the formula, and are the radiated noise levels of target 1 and target 2 respectively, is the propagation loss from target 2 to target 1, is the propagation loss from target 1 to target 2, is the ambient noise level, and These are the passive sonar array gains for target one and target two respectively.

7. The mutual detection evaluation method for underwater passive detection as claimed in claim 5, characterized in that: The step of obtaining the passive sonar array gain parameter of the target to be measured includes: Obtain the number of first passive sonar array elements of target one and the number of second passive sonar array elements of target two; Calculate the first passive sonar array gain of target one according to the number of first passive sonar array elements and the number of second passive sonar array elements and the second passive sonar array gain of target 2 : In the formula, is the number of elements of the first passive sonar array, is the number of elements of the second passive sonar array.

8. The mutual detection evaluation method for underwater passive detection as claimed in claim 5, characterized in that: The obtaining of the environmental noise level comprises: determining the environmental noise level and the environmental noise probability density function according to the historical data of the detection environment.

9. The mutual detection evaluation method for underwater passive detection according to claim 1, characterized in that: The method of calculating the first conditional probability and the second conditional probability that the first target and the second target detect each other according to the environmental noise probability density function and the signal margin parameter when the two targets to be detected do not exist includes: When the probability density function of the ambient noise conforms to the Gaussian white noise of the normal distribution, the first conditional probability of target one is calculated according to the formula And the second conditional probability of target 2 : In the formula, is the standard deviation of ambient noise, The signal detected for target 1 contains the radiation noise event of target 2. The signal detected for target 2 contains the radiation noise event of target 1. is the detection threshold.

10. A mutual detection evaluation device for underwater passive detection, characterized in that: The mutual exploration factor calculation device comprises: A signal margin calculation unit, which is used to calculate the signal margin parameters of target one and target two before detecting each other according to the target detectability characteristic parameters and target detection performance of the two targets to be detected and the distribution of environmental noise; A probability calculation unit, which is used to calculate a first conditional probability and a second conditional probability that the first target and the second target detect each other according to the environmental noise probability density function and the signal margin parameter when the two targets to be detected do not exist; An evaluation unit is used to calculate the mutual exploration factor between the first target and the second target according to the first conditional probability and the second conditional probability.

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