A method and system for estimating the time-to-closest point of approach of an underwater moving target

Abstract

The application discloses a kind of underwater moving target closest approach distance time point estimation method, it is related to underwater moving target field, by setting detection sonar in the preset range of target needing protection, the noise intensity A of underwater moving target is detected and collected by detection sonar, set the conversion relationship between noise intensity A, noise intensity P, straight line distance L, by straight line distance acquisition formula and conversion relationship formula obtains with sampling time point t as independent variable, with dependent variable of one-dimensional quadratic target equation, and using quadratic term fitting algorithm curve fitting one-dimensional quadratic target equation: set fitting function and data sequence (x i ,y i ) With the mean square error calculation formula of fitting function, and the coefficient of fitting function is obtained by solving mean square error calculation formula through data sequence (x i ,y i ), and the time point t corresponding to symmetry axis of solving fitting function is the time point that detection sonar and underwater moving target intercept is closest, and it improves the hit rate of underwater moving target.

Description

Technical Field

[0001] This invention relates to the field of underwater moving targets, and more particularly to a method and system for estimating the time point of the closest approach distance of an underwater moving target. Background Technology

[0002] With technological advancements, the application of underwater vehicles (i.e., moving underwater targets), especially unmanned underwater vehicles (UUVs), is becoming increasingly widespread. These include new types of underwater gliders, underwater ornithopters, biomimetic fish, and traditional propeller-driven UUVs, ROVs, and torpedoes. Compared to traditional naval equipment, these UUVs possess characteristics such as integrated reconnaissance and strike capabilities, strong attack capabilities, good stealth, and high hit rate, posing the greatest threat to surface and underwater ships and equipment. Therefore, how to defend against underwater vehicle reconnaissance and attacks is a crucial issue currently facing maritime development.

[0003] Existing underwater equipment primarily employs two methods for detecting and attacking various underwater vehicles: soft countermeasures and hard kill. Soft countermeasures generally involve launching air curtain missiles, jamming equipment, and acoustic decoys. By setting up false targets and increasing environmental noise, they interfere with and deceive the guidance systems of underwater vehicles, preventing them from approaching the target. However, soft countermeasures suffer from high operational requirements and uncertain defensive effectiveness. Hard kill typically involves directly firing projectiles from the surface or underwater to directly destroy approaching underwater vehicles. It has the advantages of simplicity and high effectiveness, but suffers from difficulties in detecting and locating underwater vehicles and low accuracy.

[0004] This invention employs sonar equipped with attack capabilities to be deployed around the target to be protected. By detecting the noise generated when an underwater vehicle moves, a weighted least squares curve fitting algorithm is used to estimate the time point when the underwater vehicle is closest to the intercept of the sonar. By activating the attack capability at this moment, the optimal damage effect on the underwater vehicle can be achieved. Summary of the Invention

[0005] To improve the hit rate of underwater moving targets, this invention proposes a time point estimation method for the closest approach distance of underwater moving targets. This method is based on a detection sonar, which is set within a preset range of the target to be protected and is used to detect and collect the noise intensity A of the underwater moving target. The time point at which the noise intensity A of the underwater moving target is collected is the sampling time point t. The method includes:

[0006] S1: Based on the positional relationship between the underwater moving target and the sonar, set the formula for obtaining the straight-line distance between the underwater moving target and the sonar; set the noise intensity of the underwater moving target when it moves at its highest speed as P, and set the conversion relationship between the straight-line distance L between the underwater moving target and the sonar and the noise intensity A and the noise intensity P.

[0007] S2: Obtain the formula and conversion relationship through straight-line distance, with the sampling time point t as the independent variable. A quadratic objective equation with a dependent variable;

[0008] S3: Curve fitting of the quadratic objective equation using a quadratic fitting algorithm, including:

[0009] S31: Based on the sampling time point t and the quadratic objective equation in one variable Let the sampling time point t be x i , For y i A set of data sequences (x) are collected by sonar. i ,y i ),in:

[0010] i = 1, 2, 3...m, where m is the total number of data sequences;

[0011] S32: Set the fitting function and set the data sequence (x i ,y i The formula for calculating the mean square error of the fitted function is obtained by using the data sequence (x) i ,y i Solve the formula for calculating the mean square error to obtain the coefficients of the fitted function;

[0012] S33: Obtain the axis of symmetry of the fitted function after solving, and obtain the time point t corresponding to the axis of symmetry as the time point with the closest intercept between the sonar and the underwater moving target.

[0013] Furthermore, the detection sonar includes a hydrophone and a data acquisition circuit; the hydrophone is used to detect the noise intensity A of underwater moving targets, and the data acquisition circuit is used to sample the noise intensity A detected by the hydrophone.

[0014] Further, step S1 specifically includes:

[0015] Based on the positional relationship between the underwater moving target and the detection sonar, a right triangle is formed by the hypotenuse, the first right-angled side, and the second right-angled side; the hypotenuse is the straight-line distance between the underwater moving target and the detection sonar, and the first right-angled side is the shortest straight-line distance when the underwater moving target passes the detection sonar side;

[0016] Let the velocity of the underwater moving target be V, the shortest straight-line distance between the underwater moving target and the sonar be D, and the length of the second right-angled side be F; the formula for obtaining the straight-line distance between the underwater moving target and the sonar is obtained by using the relationship between the sides of the right triangle:

[0017]

[0018] In step S1, the expression for the conversion relationship is: A = P / L.

[0019] Furthermore, in step S2, the expression for the quadratic objective equation is:

[0020]

[0021] Furthermore, in step S32, a fitting function is set, and a data sequence (x) is defined. i ,y i The formula for calculating the mean square error of the fitted function is obtained by using the data sequence (x) i ,y i Solving the mean square error formula yields the coefficients of the fitted function, specifically including:

[0022] S321: Set the fitting function as p(x) = a0 + a1x + a2x 2 , where p(x) is the noise intensity of the underwater moving target, x is the sampling time point, and a0, a1, and a2 are the coefficients of the fitting function;

[0023] S322: Set the data sequence (x) i ,y i The formula for calculating the mean square error of the fitted function is:

[0024] In the formula, p(x) i ) represents the noise intensity corresponding to the underwater moving target at the i-th sampling time point, m is the total number of data sequences that fit the fitting function, Q(a 0, a1, a2) are the mean square errors;

[0025] S323: The normal equation for the fit is obtained through the mean square error calculation formula:

[0026]

[0027] S324: Through the collected data sequence (x) i ,y i Solving the equation yields the calculated values ​​of the coefficients a0, a1, and a2 of the fitted function.

[0028] Further, in step S322: the mean square error Q(a) 0, The minimum value of a1, a2) satisfies the following condition formula:

[0029]

[0030] This invention also proposes a time-point estimation system for the closest approach distance of an underwater moving target, which is based on a detection sonar. The detection sonar is set within a preset range of the target to be protected and is used to detect and collect the noise intensity A of the underwater moving target. The time point at which the noise intensity A of the underwater moving target is collected is the sampling time point t. The system includes:

[0031] The setting module is used to set the formula for obtaining the straight-line distance between the underwater moving target and the sonar based on the positional relationship between the underwater moving target and the sonar; set the noise intensity of the underwater moving target when it moves at its maximum speed as P; and set the conversion relationship between the straight-line distance L between the underwater moving target and the sonar and the noise intensity A and the noise intensity P.

[0032] The equation acquisition module is used to obtain formulas and conversion relationships based on straight-line distance, with the sampling time point t as the independent variable. A quadratic objective equation with a dependent variable;

[0033] The fitting module is used to fit a quadratic objective equation using a quadratic fitting algorithm, including:

[0034] The acquisition unit is used to obtain data based on the sampling time point t in the quadratic objective equation and... Let the sampling time point t be x i , For y i A set of data sequences (x) are collected by sonar. i ,y i ),in:

[0035] i = 1, 2, 3...m, where m is the total number of data sequences;

[0036] The fitting unit is used to define the fitting function and the data sequence (x). i ,y i The formula for calculating the mean square error of the fitted function is obtained by using the data sequence (x) i ,y i Solve the formula for calculating the mean square error to obtain the coefficients of the fitted function;

[0037] The target time point acquisition unit is used to obtain the axis of symmetry of the fitted function after the solution is obtained, and the time point t corresponding to the axis of symmetry is the time point when the intercept between the detection sonar and the underwater moving target is closest.

[0038] Furthermore, the detection sonar includes a hydrophone and a data acquisition circuit; the hydrophone is used to detect the noise intensity A of underwater moving targets, and the data acquisition circuit is used to sample the noise intensity A detected by the hydrophone.

[0039] Furthermore, the setting module is specifically used for:

[0040] Based on the positional relationship between the underwater moving target and the detection sonar, a right triangle is formed by the hypotenuse, the first right-angled side, and the second right-angled side; the hypotenuse is the straight-line distance between the underwater moving target and the detection sonar, and the first right-angled side is the shortest straight-line distance when the underwater moving target passes the detection sonar side;

[0041] Let the velocity of the underwater moving target be V, the shortest straight-line distance between the underwater moving target and the sonar be D, and the length of the second right-angled side be F; the formula for obtaining the straight-line distance between the underwater moving target and the sonar is obtained by using the relationship between the sides of the right triangle:

[0042]

[0043] In the setting module, the expression for the conversion relationship is: A = P / L.

[0044] Furthermore, in the equation acquisition module, the expression for the quadratic objective equation is:

[0045]

[0046] Compared with the prior art, the present invention has at least the following beneficial effects:

[0047] This invention involves setting up a detection sonar within a preset range of the target to be protected. The sonar detects and collects the noise intensity A of the underwater moving target. A formula for obtaining the straight-line distance between the underwater moving target and the detection sonar is established. A conversion relationship is defined between noise intensity A, noise intensity P, and straight-line distance L. The straight-line distance is obtained using the formula and conversion relationship, with the sampling time point t as the independent variable. The objective function is a quadratic equation with a dependent variable, and a quadratic fitting algorithm is used to fit the quadratic objective function to a curve: the fitting function and the data sequence (x) are defined. i ,y i The formula for calculating the mean square error of the fitted function and the data sequence (x) is used. i ,y i The coefficients of the fitting function are obtained by solving the mean square error calculation formula. The time point t corresponding to the axis of symmetry of the fitted function is the time point when the intercept between the detection sonar and the underwater moving target is closest. This avoids many problems in the existing technology, such as high usage requirements and uncertain defense effect when using soft countermeasures, and high difficulty and low accuracy when using hard kill detection and positioning. Moreover, this invention can be realized by setting up the detection sonar within a preset range of the target to be protected, which greatly reduces the attack cost and greatly improves the hit rate of underwater moving targets. Attached Figure Description

[0048] Figure 1 Flowchart of a method for estimating the time point of the closest approach distance of an underwater moving target;

[0049] Figure 2 A block diagram of a system for estimating the time point of closest approach distance of an underwater moving target;

[0050] Figure 3 This is a schematic diagram showing the relative position of an underwater vehicle approaching a detection sonar. Detailed Implementation

[0051] The following are specific embodiments of the present invention, which are described in conjunction with the accompanying drawings. However, the present invention is not limited to these embodiments.

[0052] Example 1

[0053] Curve fitting algorithms are data processing algorithms that use continuous curves to approximate the functional relationship between the coordinates of discrete points on a plane.

[0054] The weighted least squares curve fitting algorithm is an algorithm that, based on the conventional curve fitting algorithm, weights the input according to the weight of the influence of the input error on the output result, and uses the least squares method to calculate the output in order to reduce the final error.

[0055] To improve the hit rate against moving underwater targets and address the numerous problems of existing soft-countermeasures technologies (high usage requirements and uncertain defensive effectiveness) and hard-kill detection and positioning technologies (high difficulty and low accuracy), such as... Figure 1 As shown, this invention proposes a method for estimating the closest approach distance of an underwater moving target at a specific time point. This method is based on a detection sonar, which is positioned within a preset range of the target to be protected. The sonar is used to detect and collect the noise intensity A of the underwater moving target. The time point at which the noise intensity A is collected is the sampling time point t. The detection sonar includes a hydrophone and a data acquisition circuit. The hydrophone is used to detect the noise intensity A of the underwater moving target, and the data acquisition circuit is used to sample the noise intensity A detected by the hydrophone. In this embodiment, the prerequisite for the time point estimation method is that the underwater moving target moves in a straight line at a constant speed when approaching the detection sonar.

[0056] The method includes:

[0057] S1: Based on the positional relationship between the underwater moving target and the sonar, set the formula for obtaining the straight-line distance between the underwater moving target and the sonar; set the noise intensity of the underwater moving target when it moves at its highest speed as P, and set the conversion relationship between the straight-line distance L between the underwater moving target and the sonar and the noise intensity A and the noise intensity P.

[0058] The specific steps of S1 are as follows:

[0059] like Figure 3 As shown, a right triangle is formed by the hypotenuse, the first right-angled side, and the second right-angled side based on the positional relationship between the underwater moving target (underwater vehicle) and the detection sonar; the hypotenuse is the straight-line distance between the underwater moving target and the detection sonar, and the first right-angled side is the shortest straight-line distance when the underwater moving target passes the detection sonar side;

[0060] Let the velocity of the underwater moving target be V, the shortest straight-line distance between the underwater moving target and the sonar be D, and the length of the second right-angled side be F; the formula for obtaining the straight-line distance between the underwater moving target and the sonar is obtained by using the relationship between the sides of the right triangle:

[0061]

[0062] In step S1, the expression for the conversion relationship is: A = P / L.

[0063] In this embodiment, the length of the second right-angled side is F = 200.

[0064] S2: Obtain the formula and conversion relationship through straight-line distance, with the sampling time point t as the independent variable. A quadratic objective equation with a dependent variable;

[0065] In step S2, the expression for the quadratic objective equation is:

[0066]

[0067] In the quadratic objective equation of this embodiment, D, V, and P are uncertain. However, since the underwater moving target's velocity V is constant during its close approach to and passage through the sonar, and V is constant, P also remains constant. Meanwhile, the value of D is a definite quantity during a single detection process; therefore, all three can be treated as constants. Thus, the quadratic objective equation uses the sampling time point t as the independent variable, with... It is a quadratic equation with one variable as the dependent variable.

[0068] In this embodiment, the quadratic term fitting algorithm, which has the least computational cost among curve fitting methods, is used to perform curve fitting on the above-mentioned univariate quadratic objective equation.

[0069] S3: Curve fitting of the quadratic objective equation using a quadratic fitting algorithm, including:

[0070] Let p(x) = ax 2+bx+c; where p(x) is the noise intensity of the underwater moving target, and x is the sampling time point. The quadratic fitting equation can be obtained by solving the coefficients a, b, and c. The specific fitting method is as follows:

[0071] S31: Based on the sampling time point t and the quadratic objective equation in one variable Let the sampling time point t be x i , For y i A set of data sequences (x) are collected by sonar. i ,y i ),in:

[0072] i = 1, 2, 3...m, where m is the total number of data sequences; the sampling time point t is the relative time when the data acquisition circuit samples, which is a known quantity;

[0073] Theoretically, curve fitting of a quadratic equation requires only three points, but considering the impact of noise and the accuracy of the fitting, it is advisable to use as many data points as possible. It is important to emphasize that, since this invention uses the time point t corresponding to the axis of symmetry of the solved fitting function as the time point with the closest intercept between the sonar and the underwater moving target, even in the data (x...) used for curve fitting... i ,y i The amount of data is relatively small, so even if the data sequence used for curve fitting does not include the data corresponding to the time point when the underwater moving target is closest to the intercept of the detection sonar, it still does not affect the estimation of the time point when the intercept of the detection sonar and the underwater moving target is closest. Therefore, the present invention can greatly improve the calculation speed.

[0074] S32: Set the fitting function and set the data sequence (x i ,y i The formula for calculating the mean square error of the fitted function is obtained by using the data sequence (x) i ,y i Solve the formula for calculating the mean square error to obtain the coefficients of the fitted function;

[0075] In step S32, a fitting function is set, and a data sequence (x) is defined. i ,y i The formula for calculating the mean square error of the fitted function is obtained by using the data sequence (x) i ,y i Solving the mean square error formula yields the coefficients of the fitted function, specifically including:

[0076] S321: Set the fitting function (quadratic equation) as p(x) = a0 + a1x + a2x 2, where p(x) is the noise intensity of the underwater moving target, x is the sampling time point, and a0, a1, and a2 are the coefficients of the fitting function;

[0077] S322: Draw the data sequence (x) i ,y i The formula for calculating the mean square error of the fitted function is:

[0078] In the formula, p(x) i ) represents the noise intensity corresponding to the underwater moving target at the i-th sampling time point, m is the total number of data sequences that fit the fitting function, Q(a 0, a1, a2) are the mean square errors;

[0079] By the principle of extrema of a quadratic equation, the mean square error Q(a) 0, The minimum value of a1, a2) should satisfy the following condition formula:

[0080]

[0081] S323: The normal equation for the fit is obtained through the mean square error calculation formula (specifically, the normal equation for the fit of the univariate quadratic polynomial function is obtained by simplifying the condition formula):

[0082]

[0083] S324: Through the collected data sequence (x) i ,y i Solving the equation yields the calculated values ​​of the coefficients a0, a1, and a2 of the fitted function under the condition of minimum mean square error.

[0084] S33: Obtain the axis of symmetry of the fitted function after solving, and obtain the time point t corresponding to the axis of symmetry as the time point with the closest intercept between the sonar and the underwater moving target.

[0085] The solved fitting function is simplified to at 2 +bt+c=y, the axis of symmetry of the equation is t=b / 2a, the value of y corresponding to the axis of symmetry is the vertex of the curve; the time point t corresponding to the axis of symmetry is the time point when the intercept between the sonar and the underwater moving target is closest.

[0086] This invention involves setting up a detection sonar within a preset range of the target to be protected. The sonar detects and collects the noise intensity A of the underwater moving target. A formula for obtaining the straight-line distance between the underwater moving target and the detection sonar is established. A conversion relationship is defined between noise intensity A, noise intensity P, and straight-line distance L. The straight-line distance is obtained using the formula and conversion relationship, with the sampling time point t as the independent variable. The objective function is a quadratic equation with a dependent variable, and a quadratic fitting algorithm is used to fit the quadratic objective function to a curve: the fitting function and the data sequence (x) are defined. i ,y i The formula for calculating the mean square error of the fitted function and the data sequence (x) is used. i ,y i The coefficients of the fitting function are obtained by solving the mean square error calculation formula. The time point t corresponding to the axis of symmetry of the fitted function is the time point when the intercept between the detection sonar and the underwater moving target is closest. This avoids many problems in the existing technology, such as high usage requirements and uncertain defense effect when using soft countermeasures, and high difficulty and low accuracy when using hard kill detection and positioning. Moreover, this invention can be realized by setting up the detection sonar within a preset range of the target to be protected, which greatly reduces the attack cost and greatly improves the hit rate of underwater moving targets.

[0087] Example 2

[0088] like Figure 2 As shown, this invention also proposes a time point estimation system for the closest approach distance of an underwater moving target, which is based on a detection sonar. The detection sonar is set within a preset range of the target to be protected and is used to detect and collect the noise intensity A of the underwater moving target. The time point at which the noise intensity A of the underwater moving target is collected is the sampling time point t. The detection sonar includes a hydrophone and a data acquisition circuit. The hydrophone is used to detect the noise intensity A of the underwater moving target, and the data acquisition circuit is used to sample the noise intensity A detected by the hydrophone. The system includes:

[0089] The setting module is used to set the formula for obtaining the straight-line distance between the underwater moving target and the sonar based on the positional relationship between the underwater moving target and the sonar; set the noise intensity of the underwater moving target when it moves at its maximum speed as P; and set the conversion relationship between the straight-line distance L between the underwater moving target and the sonar and the noise intensity A and the noise intensity P.

[0090] The setting module is specifically used for:

[0091] Based on the positional relationship between the underwater moving target and the detection sonar, a right triangle is formed by the hypotenuse, the first right-angled side, and the second right-angled side; the hypotenuse is the straight-line distance between the underwater moving target and the detection sonar, and the first right-angled side is the shortest straight-line distance when the underwater moving target passes the detection sonar side;

[0092] Let the velocity of the underwater moving target be V, the shortest straight-line distance between the underwater moving target and the sonar be D, and the length of the second right-angled side be F; the formula for obtaining the straight-line distance between the underwater moving target and the sonar is obtained by using the relationship between the sides of the right triangle:

[0093]

[0094] In the setting module, the expression for the conversion relationship is: A = P / L.

[0095] The equation acquisition module is used to obtain formulas and conversion relationships based on straight-line distance, with the sampling time point t as the independent variable. A quadratic objective equation with a dependent variable;

[0096] In the equation acquisition module, the expression for the quadratic objective equation is:

[0097]

[0098] The fitting module is used to fit a quadratic objective equation using a quadratic fitting algorithm, including:

[0099] The acquisition unit is used to obtain data based on the sampling time point t in the quadratic objective equation and... Let the sampling time point t be x i , For y i A set of data sequences (x) are collected by sonar. i ,y i ),in:

[0100] i = 1, 2, 3...m, where m is the total number of data sequences;

[0101] The fitting unit is used to define the fitting function and the data sequence (x). i ,y i The formula for calculating the mean square error of the fitted function is obtained by using the data sequence (x) i ,y i Solve the formula for calculating the mean square error to obtain the coefficients of the fitted function;

[0102] The target time point acquisition unit is used to obtain the axis of symmetry of the fitted function after the solution is obtained, and the time point t corresponding to the axis of symmetry is the time point when the intercept between the detection sonar and the underwater moving target is closest.

[0103] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0104] Furthermore, in this invention, descriptions involving terms such as "first," "second," and "a" are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0105] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0106] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

Claims

1. A method for estimating the time point of closest approach distance of an underwater moving target, characterized in that, It estimates based on a detection sonar, which is set within a preset range of the target to be protected, and is used to detect and collect the noise intensity of underwater moving targets. Among them, the noise intensity of underwater moving targets was collected. The time point is the sampling time point The method includes: S1: Based on the positional relationship between the underwater moving target and the sonar, a formula for obtaining the straight-line distance between the underwater moving target and the sonar is established; the noise intensity of the underwater moving target at its maximum speed is set as... And set the straight-line distance between the underwater moving target and the detection sonar. With noise intensity Noise intensity Conversion formulas between them; S2: Obtain the sampling time point by using the formula and conversion relationship based on the straight-line distance. As the independent variable, with The objective function is a quadratic equation with the dependent variable as the dependent variable; in step S2, the expression of the quadratic objective function is: In the formula, This represents the shortest straight-line distance when an underwater moving target passes the detection sonar side; Indicates the speed of an underwater moving target; S3: Curve fitting of the quadratic objective equation using a quadratic fitting algorithm, including: S31: Based on the sampling time points in the quadratic objective equation and The relationship between sampling time points for , for A set of data sequences was collected by detecting sonar. , ),in: , This represents the total number of data sequences. S32: Set the fitting function and set the data sequence ( , The formula for calculating the mean square error of the fitted function is obtained through the data sequence ( , Solve the formula for calculating the mean square error to obtain the coefficients of the fitted function; S33: Obtain the axis of symmetry of the fitted function after solving, and obtain the time point corresponding to the axis of symmetry as the time point with the closest intercept between the sonar and the underwater moving target.

2. The method for estimating the time point of closest approach distance of an underwater moving target according to claim 1, characterized in that, The detection sonar includes a hydrophone and a data acquisition circuit; the hydrophone is used to detect the noise intensity of underwater moving targets. The data acquisition circuit is used to measure the noise intensity detected by the hydrophone. Perform sampling.

3. The method for estimating the time point of closest approach distance of an underwater moving target according to claim 2, characterized in that, The specific steps of S1 are as follows: Based on the positional relationship between the underwater moving target and the detection sonar, a right triangle is formed by the hypotenuse, the first right-angled side, and the second right-angled side; the hypotenuse is the straight-line distance between the underwater moving target and the detection sonar, and the first right-angled side is the shortest straight-line distance when the underwater moving target passes the detection sonar side; Let the velocity of the underwater moving target be... The shortest straight-line distance when an underwater moving target passes the detection sonar side is The length of the second right-angled leg is The formula for obtaining the straight-line distance between an underwater moving target and the sonar, derived from the relationships between the sides of a right triangle, is as follows: ； In step S1, the expression for the conversion relation is: .

4. The method for estimating the time point of closest approach of an underwater moving target according to claim 3, characterized in that, In step S32, a fitting function is set, and a data sequence is set ( , The formula for calculating the mean square error of the fitted function is obtained through the data sequence ( , Solving the mean square error formula yields the coefficients of the fitted function, specifically including: S321: Set the fitting function as... ,in That is, the noise intensity of underwater moving targets. For the sampling time point, , , All are coefficients of the fitted function; S322: Set data sequence ( , The formula for calculating the mean square error of the fitted function is: In the formula, This represents the noise intensity corresponding to the underwater moving target at the i-th sampling time point. The total number of data sequences to fit the fitting function. Mean square error; S323: The normal equation for the fit is obtained through the mean square error calculation formula: ； S324: Through the collected data sequence ( , Solving the normal equations yields the coefficients of the fitted function. , , The calculated value.

5. The method for estimating the time point of closest approach of an underwater moving target according to claim 4, characterized in that, In step S322: mean square error The minimum value satisfies the following formula: 。 6. A time point estimation system for the closest approach distance of an underwater moving target, characterized in that, It estimates based on a detection sonar, which is set within a preset range of the target to be protected, and is used to detect and collect the noise intensity of underwater moving targets. Among them, the noise intensity of underwater moving targets was collected. The time point is the sampling time point The system includes: The setting module is used to set the formula for obtaining the straight-line distance between the underwater moving target and the sonar based on the positional relationship between the underwater moving target and the sonar; and to set the noise intensity of the underwater moving target when it moves at its maximum speed. And set the straight-line distance between the underwater moving target and the detection sonar. With noise intensity Noise intensity Conversion formulas between them; The equation acquisition module is used to obtain formulas and conversion relationships based on straight-line distances, and to obtain the sampling time points. As the independent variable, with The objective function is a quadratic equation in one variable, where the dependent variable is the variable; the expression of the quadratic objective function is: In the formula, This represents the shortest straight-line distance when an underwater moving target passes the detection sonar side; Indicates the speed of an underwater moving target; The fitting module is used to fit a quadratic objective equation using a quadratic fitting algorithm, including: The acquisition unit is used to collect data based on the sampling time points in the quadratic objective equation. and The relationship between sampling time points for , for A set of data sequences was collected by detecting sonar. , ),in: , This represents the total number of data sequences. The fitting unit is used to set the fitting function and the data sequence. , The formula for calculating the mean square error of the fitted function is obtained through the data sequence ( , Solve the formula for calculating the mean square error to obtain the coefficients of the fitted function; The target time point acquisition unit is used to obtain the axis of symmetry of the fitted function after solving, and to obtain the time point corresponding to the axis of symmetry as the time point with the closest intercept between the detection sonar and the underwater moving target.

7. The time point estimation system for the closest approach distance of an underwater moving target according to claim 6, characterized in that, The detection sonar includes a hydrophone and a data acquisition circuit; the hydrophone is used to detect the noise intensity of underwater moving targets. The data acquisition circuit is used to measure the noise intensity detected by the hydrophone. Perform sampling.

8. The time point estimation system for the closest approach distance of an underwater moving target according to claim 7, characterized in that, The setting module is specifically used for: Based on the positional relationship between the underwater moving target and the detection sonar, a right triangle is formed by the hypotenuse, the first right-angled side, and the second right-angled side; the hypotenuse is the straight-line distance between the underwater moving target and the detection sonar, and the first right-angled side is the shortest straight-line distance when the underwater moving target passes the detection sonar side; Let the velocity of the underwater moving target be... The shortest straight-line distance when an underwater moving target passes the detection sonar side is The length of the second right-angled leg is The formula for obtaining the straight-line distance between an underwater moving target and the sonar, derived from the relationships between the sides of a right triangle, is as follows: ； In the setting module, the expression for the conversion relation is: .

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