CN115061483B - Underwater target state cooperative estimation method based on detection configuration - Google Patents

Underwater target state cooperative estimation method based on detection configuration Download PDF

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CN115061483B
CN115061483B CN202210562033.XA CN202210562033A CN115061483B CN 115061483 B CN115061483 B CN 115061483B CN 202210562033 A CN202210562033 A CN 202210562033A CN 115061483 B CN115061483 B CN 115061483B
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CN115061483A (en
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赵恩娇
张可
林学航
元博
张钰欣
曾志镪
尚雪
赵玉新
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Harbin Engineering University
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    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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    • G05D1/04—Control of altitude or depth
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Abstract

The utility model provides a detection configuration-based underwater target state collaborative estimation method, which relates to the technical field of underwater unmanned aircraft formation control and target state estimation, and aims at solving the problem that a single submarine can have larger positioning error in continuous underwater long voyage in the prior art. According to the method, the centralized communication topological structure is utilized, pure azimuth information of a plurality of UUV detection nodes is concentrated and expanded, the defect that the observability of a single UUV node observation equation is not strong is overcome, the problem that a single submarine can have larger positioning error when continuously sailing underwater is solved, estimation precision is improved, and convergence time is shortened.

Description

Underwater target state cooperative estimation method based on detection configuration
Technical Field
The invention relates to the technical field of underwater unmanned aircraft formation control and target state estimation, in particular to an underwater target state collaborative estimation method based on a detection configuration.
Background
With the increasing development of ocean exploration and development technologies, unmanned underwater vehicles play an important role in ocean exploration. Due to the complexity of the underwater environment, a single submarine can have larger positioning errors when continuously sailing under water, and certain task requirements can not be met. Therefore, the cooperation of the submarine and the plurality of UUV can complete the task of detecting and tracking the target by continuous underwater long-distance navigation.
In recent years, with the improvement of the concealment performance and the enhancement of the maneuvering performance of underwater objects, uncertainty exists in the detection equipment of submarines. The detection range of the submarine can be enlarged by a cooperative system consisting of the submarine and a plurality of UUV. The cooperative system takes a plurality of UUV as the front output, and the submarine can realize the short-range omnibearing warning reconnaissance so as to effectively remove the threat of the submarine. When the UUV is used for defending against the submarine, the UUV can be used as a deception target or a impersonation target to shield the action of the submarine, and the UUV can also simulate the acoustic characteristics of the submarine to directly generate a simulated acoustic signal of the submarine, so that the purposes of confusing enemy detection equipment and protecting the submarine are achieved. The submarine is used as a rear remote control command, and a control command is transmitted to the UUV through the communication equipment. The multi-node co-positioning and tracking system composed of the submarine and the UUV has the advantages of strong adaptability, high detection efficiency and the like, and has a plurality of remarkable advantages in the aspects of military, ocean development and the like, so that the development of the multi-node co-positioning and tracking system is valued in all countries of the world.
Disclosure of Invention
The purpose of the invention is that: aiming at the problem that a single submarine can have larger positioning error in continuous underwater long voyage in the prior art, the underwater target state cooperative estimation method based on the detection configuration is provided.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the underwater target state cooperative estimation method based on the detection configuration comprises a formation step and an estimation step;
the formation step specifically comprises the following steps:
step 1: acquiring the azimuth of the target by using sonar, and establishing a multi-UUV formation control model according to the azimuth of the target;
step 2: acquiring formation desired formation delta i And first discovering the position of the UUV of the target, and then forming the expected formation delta according to the position of the UUV of the target which is first discovered i The multi-UUV formation control model designs a formation controller, and forms the multi-UUV according to the formation controller;
the estimating step specifically comprises the following steps:
step one: establishing a motion model of the target;
step two: designing an extended state observer, and then carrying out disturbance estimation on the target by using the extended state observer to obtain a disturbance estimation result of the target;
step three: estimating a motion model of the target by using a disturbance estimation result of the target to obtain an accurate estimation result of the target;
step four: obtaining a target motion state according to an accurate estimation result of the target;
step five: estimating the azimuth of the target by adopting a square root volume Kalman filtering method;
step six: acquiring noise, and constructing an observation equation according to the motion state of the target, the estimated azimuth of the target and the noise;
step seven: and obtaining an extended observation equation according to the observation equation and adopting a centralized communication topological structure, thereby completing cooperative estimation.
Further, the multi-UUV formation control model is expressed as:
Figure BDA0003656971670000021
wherein X is i 、V i 、A i Representing the expected position, velocity and acceleration of the ith UUV in three dimensions,
Figure BDA0003656971670000022
representing the desired position X i Derivative of>
Figure BDA0003656971670000023
Representing velocity V i Is a derivative of (a).
Further, the formation controller is expressed as:
Figure BDA0003656971670000024
wherein, the subscript m represents UUV number of the target found first, and gamma represents feedback control gain, K v Indicating the speed error control gain, K p Indicating the position error control gain, a ij Representing parameters of a communication topology weight matrix coefficient, c representing parameters of a consistency protocol, N i Representing a set of UUV nodes, X j Representing the position of the J-th UUV node, delta j Representing a desired formation of a J-th UUV node, V j Representing the speed of the J-th UUV node.
Further, the motion model of the target is expressed as:
Figure BDA0003656971670000031
wherein X is T 、V T 、A T Respectively representing the position, the speed and the acceleration in the three-dimensional space,
Figure BDA0003656971670000032
representing the position X of an object T Derivative of>
Figure BDA0003656971670000033
Representing the target speed V T Is a derivative of (a).
Further, the extended state observer is expressed as:
Figure BDA0003656971670000034
wherein beta is 1 、β 2 And beta 3 The gain parameter is represented by a value of,
Figure BDA0003656971670000035
representation pair->
Figure BDA0003656971670000036
Estimate of->
Figure BDA0003656971670000037
Representing the target speed V T Estimated value of ∈10->
Figure BDA0003656971670000038
Representing the target position X T Estimated value of ∈10->
Figure BDA0003656971670000039
Representing target acceleration A T Estimated value of g 1 ()、g 2 ()、g 3 () Representing a function of observer stability.
Further, the estimating the motion model of the target by using the disturbance estimation result of the target is expressed as:
Figure BDA00036569716700000310
further, the estimated position of the target is expressed as:
Figure BDA00036569716700000311
wherein q εi Indicating the high and low angles, q βi Indicating azimuth, x T 、y T 、h T Representing the position in three-dimensional coordinates of the object, x si 、y si 、h si Representing the position of the submarine or UUV in three dimensions.
Further, the observation equation is expressed as:
Figure BDA0003656971670000041
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0003656971670000042
white noise representing high and low angles, +.>
Figure BDA0003656971670000043
White noise representing azimuth, h i (X T ) Representing the location function of the object.
Further, the extended observation equation is expressed as:
Figure BDA0003656971670000044
where η represents a set of location functions for which all UUV nodes detect a target.
The beneficial effects of the invention are as follows:
according to the collaborative estimation method for the underwater dynamic target state, provided by the application, the submarine (central node) and a plurality of Underwater Unmanned Vehicles (UUV) nodes form, the submarine sends a control instruction to enable each UUV to complete the expected formation, each UUV utilizes azimuth measurement information to carry out collaborative estimation on the enemy target, effective estimation on the underwater dynamic target state is achieved, and necessary conditions are provided for a collaborative system to complete underwater tasks. According to the method, the centralized communication topological structure is utilized, pure azimuth information of a plurality of UUV detection nodes is concentrated and expanded, the defect that the observability of a single UUV node observation equation is not strong is overcome, the problem that a single submarine can have larger positioning error when continuously sailing underwater is solved, estimation precision is improved, and convergence time is shortened.
Drawings
FIG. 1 is a flow chart of the present application;
FIG. 2 is a system block diagram of the present application;
fig. 3 is a diagram of a multi UUV formation transformation;
FIG. 4 is a schematic illustration of a formation desired formation;
FIG. 5 is a schematic diagram of an estimated value of a target position;
FIG. 6 is a schematic diagram of an estimated value of a target speed;
fig. 7 is a schematic diagram of an estimated value of the target acceleration.
Detailed Description
It should be noted in particular that, without conflict, the various embodiments disclosed herein may be combined with each other.
The first embodiment is as follows: referring to fig. 1, a specific description is given of the present embodiment, which is a cooperative estimation method for an underwater target state based on a detection configuration, where the cooperative estimation method includes a formation step and an estimation step;
the formation step specifically comprises the following steps:
step 1: acquiring the azimuth of the target by using sonar, and establishing a multi-UUV formation control model according to the azimuth of the target;
step 2: acquiring formation desired formation delta i And first discovering the position of the UUV of the target, and then forming the expected formation delta according to the position of the UUV of the target which is first discovered i The multi-UUV formation control model designs a formation controller, and forms the multi-UUV according to the formation controller;
the estimating step specifically comprises the following steps:
step one: establishing a motion model of the target;
step two: designing an extended state observer, and then carrying out disturbance estimation on the target by using the extended state observer to obtain a disturbance estimation result of the target;
step three: estimating a motion model of the target by using a disturbance estimation result of the target to obtain an accurate estimation result of the target;
step four: obtaining a target motion state according to an accurate estimation result of the target;
step five: estimating the azimuth of the target by adopting a square root volume Kalman filtering method;
step six: acquiring noise, and constructing an observation equation according to the motion state of the target, the estimated azimuth of the target and the noise;
step seven: and obtaining an extended observation equation according to the observation equation and adopting a centralized communication topological structure, thereby completing cooperative estimation.
The underwater target collaborative estimation and multi-UUV formation control research method can automatically complete expected formation, has high target positioning and tracking precision in a hidden environment, enlarges the detection range of the target and can effectively reduce cost, and assists the submarine to complete underwater combat tasks.
Examples:
the multi-underwater unmanned vehicle tracking and formation control system structure combined with fig. 1 and 2 comprises: 1 submarine and 2 UUVs. The cooperative system formed by the submarine and the UUV comprises a central processing unit, a detection module, a communication module and an execution module. The detection module collects the state and surrounding environment information through the sensor and sends the information to a central processing unit in the submarine for information fusion; the communication module is responsible for carrying out information interaction between the submarine and each UUV; the central processing unit gives corresponding execution instructions to the submarine according to the sensor information given by the detection module and the cooperative elements given by the module; the execution module is used for responding corresponding actions of each UUV according to the formation and control instructions given by the central processing unit.
It can be seen in conjunction with fig. 3 and 4 that the UUV that first discovered the target ensures that the target is continuously detected. And simultaneously taking the submarines as the geometric centers of the formation formations, taking the geometric centers as references to give out expected positions of the other UUV, and finally adjusting the UUV positions of the targets found first after the submarines and the other UUV reach the expected positions, so that the formation formations are formed, and the submarines and the UUV can detect the targets. In fig. 3, 1 submarine and 2 UUVs are used as objects, node No. 1 is a submarine, node No. 2 and node No. 3 are UUVs, respectively, showing that node No. 2 and node No. 3 first find a target, the submarine controls another UUV to form a formation, and the process requires that the UUV first find the target finally perform position adjustment. Finally, the problem of formation control is solved by combining the consistency theory of multiple agents, and the formation controller (1) can realize the maintenance control of formation.
Figure BDA0003656971670000061
The premise of the target state estimation is to establish a target maneuver model matched with the actual maneuver of the target, and the maneuver currently performed by the target needs to be assumed. The present design regards the acceleration of the target as a disturbance term that causes changes in the target position and velocity, and uses the extended state observer technique to estimate this disturbance. Therefore, the extended state observer is built in the target tracking model, and no assumption can be made on the maneuvering condition of the target, so that the model has universality.
The general expression of the motion model of the object is expression (2).
Figure BDA0003656971670000062
Wherein X is T 、V T 、A T Respectively representing the position, the speed and the acceleration in the three-dimensional space. In order to estimate the motion state of the target, a filter model needs to be built according to equation (2). Due to acceleration A of the target T The form is changeable, and a single model is difficult to match with the actual A T Creating a problem of model mismatch and thus employing a multi-model solution. The multi-model scheme solves the problem of model matching to a certain extent, and also brings the problems of large calculation amount, information fusion among multiple models and the like, and has a complex form. The scheme adopts an extended state observer to assist in establishing a filtering model, so that the filtering model has the actual effect of multiple models. Due to acceleration A T The form is varied so it is treated as a disturbance and an extended state observer is used to estimate it. An extended state observer is established for the system (2) as shown in formula (3).
Figure BDA0003656971670000063
In the observer (3) the light source is arranged,
Figure BDA0003656971670000064
representing the estimation of the pair, gain parameter beta 1 ～β 3 Function g 1 ()～g 3 () Is required to ensure that the observer is stable. The observer (3) can be used for the A in the original system T A good estimate is achieved, so that by means of the combination of (2) and (3) a closed-loop model (4) can be obtained. Observer output->
Figure BDA0003656971670000071
And true A T Although deviation exists between the two, on one hand, the observer is stable, the deviation gradually converges, the model is smaller and smaller, and the model is more accurate; on the other hand, the deviation is also regarded as a part of noise, and the estimation accuracy is improved by using the observed value. />
Figure BDA0003656971670000072
In connection with fig. 5, 6 and 7, the state (position, velocity, acceleration) of the object is not measured directly, but only the azimuth information. The purely azimuthal information makes the equation less observable. Therefore, observation information needs to be added according to pure azimuth information and node information, so that observability is enhanced. Since the observation equation is nonlinear, a nonlinear estimation method is required to estimate the state of the target. The square root volume Kalman filtering method is adopted based on the target tracking algorithm, so that matrix inversion operation can be avoided, noise characteristics are not required, and the method is relatively suitable for scenes with strong nonlinearity and large state dimension.
Figure BDA0003656971670000073
Equation (5) defines the azimuth measurement of the target by the ith UUV (high-low angle q εi And azimuth q βi ). It can be seen that the elevation and azimuth angles are relative to the target X T ＝[x T y T h T ] T And UUV position X s ＝[x s y s h s ] T Is a non-linear function of (2). Let the measurement noise be gaussian white noise. A new observation equation can be obtained as shown in equation (6).
Figure BDA0003656971670000074
In observation equation (6), it is difficult to complete state estimation of a target by means of a single UUV. Considering that the communication structure of the submarine and the UUV is centralized, the research scheme provides the following method for enhancing the observability of the observation equation according to the centralized characteristic.
And adopting a centralized communication topological structure, and sending the azimuth information of the target to the central node by all UUV nodes. Setting the high and low angles and azimuth angles of the target detected by the ith UUV node as q respectively εi And q βi . Then the extended observation equation is
Figure BDA0003656971670000081
Where m is the UUV number from which the target can be detected. It can be seen that the expression (7) is easy to expand, and the observed noise matrix expression after expansion is ρ=diag [ R ] 1 R 2 … R m ]。
By utilizing a centralized communication topological structure and carrying out centralized expansion on pure azimuth information of a plurality of UUV detection nodes, the defect that the observation equation of a single UUV node is not strong in observability is overcome, and the method is beneficial to improving estimation accuracy and shortening convergence time.
It should be noted that the detailed description is merely for explaining and describing the technical solution of the present invention, and the scope of protection of the claims should not be limited thereto. All changes which come within the meaning and range of equivalency of the claims and the specification are to be embraced within their scope.

Claims (6)

1. The underwater target state cooperative estimation method based on the detection configuration is characterized by comprising a formation step and an estimation step;
the formation step specifically comprises the following steps:
step 1: acquiring the azimuth of the target by using sonar, and establishing a multi-UUV formation control model according to the azimuth of the target;
step 2: acquiring formation desired formation delta i And first discovering the position of the UUV of the target, and then forming the expected formation delta according to the position of the UUV of the target which is first discovered i The multi-UUV formation control model designs a formation controller, and forms the multi-UUV according to the formation controller;
the estimating step specifically comprises the following steps:
step one: establishing a motion model of the target;
step two: designing an extended state observer, and then carrying out disturbance estimation on the target by using the extended state observer to obtain a disturbance estimation result of the target;
step three: estimating a motion model of the target by using a disturbance estimation result of the target to obtain an accurate estimation result of the target;
step four: obtaining a target motion state according to an accurate estimation result of the target;
step five: estimating the azimuth of the target by adopting a square root volume Kalman filtering method;
step six: acquiring noise, and constructing an observation equation according to the motion state of the target, the estimated azimuth of the target and the noise;
step seven: according to the observation equation and adopting a centralized communication topological structure, an extended observation equation is obtained, and then cooperative estimation is completed;
the estimated position of the target is expressed as:
Figure FDA0004154041190000011
wherein q εi Indicating the high and low angles, q βi Indicating azimuth, x T 、y T 、h T Representing the position in three-dimensional coordinates of the object, x si 、y si 、h si Representing the position of the submarine or UUV in three-dimensional coordinates;
the observation equation is expressed as:
Figure FDA0004154041190000021
wherein V is qεi White noise representing high and low angles is present,
Figure FDA0004154041190000027
white noise representing azimuth, h i (X T ) A location function representing the target;
the extended observation equation is expressed as:
Figure FDA0004154041190000022
where η represents a set of location functions for which all UUV nodes detect a target.
2. The underwater target state cooperative estimation method based on the detection configuration as claimed in claim 1, wherein the multi-UUV formation control model is expressed as:
Figure FDA0004154041190000023
wherein X is i 、V i 、A i Representing the expected position, velocity and acceleration of the ith UUV in three dimensions,
Figure FDA0004154041190000024
representing the desired position X i Derivative of>
Figure FDA0004154041190000025
Representing velocity V i Is a derivative of (a).
3. A method of collaborative estimation of underwater target state based on a detected configuration according to claim 2, characterized in that the formation controller is expressed as:
Figure FDA0004154041190000026
wherein, the subscript m represents UUV number of the target found first, and gamma represents feedback control gain, K v Indicating the speed error control gain, K p Indicating the position error control gain, a ij Representing parameters of a communication topology weight matrix coefficient, c representing parameters of a consistency protocol, N i Representing a set of UUV nodes, X j Representing the position of the J-th UUV node, delta j Representing a desired formation of a J-th UUV node, V j Representing the speed of the J-th UUV node.
4. A method for collaborative estimation of underwater target state based on a detected configuration according to claim 3 wherein the motion model of the target is expressed as:
Figure FDA0004154041190000031
wherein X is T 、V T 、A T Respectively representing the position, the speed and the acceleration in the three-dimensional space,
Figure FDA0004154041190000032
representing the position X of an object T Derivative of>
Figure FDA0004154041190000033
Representing the target speed V T Is a derivative of (a).
5. The underwater target state cooperative estimation method based on the detection configuration according to claim 4, wherein the extended state observer is expressed as:
Figure FDA0004154041190000034
wherein beta is 1 、β 2 And beta 3 The gain parameter is represented by a value of,
Figure FDA0004154041190000035
representation pair->
Figure FDA0004154041190000036
Estimate of->
Figure FDA0004154041190000037
Representing the target speed V T Estimated value of ∈10->
Figure FDA0004154041190000038
Representing the target position X T Estimated value of ∈10->
Figure FDA0004154041190000039
Representing target acceleration A T Estimated value of g 1 ()、g 2 ()、g 3 () Representing a function of observer stability.
6. The collaborative estimation method for underwater target state based on detection configuration according to claim 5, wherein the estimating the motion model of the target using the disturbance estimation result of the target is expressed as:
Figure FDA00041540411900000310
/>
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