CN112525201A - Underwater target tracking method based on electromagnetic field characteristic multi-information fusion - Google Patents
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Abstract
The invention relates to an underwater target tracking method based on electromagnetic field characteristic multi-information fusion, wherein a plurality of magnetic field sensors and electric field measuring electrodes are arranged in an array form, after three-direction coordinate position initial solutions, magnetic dipole moments and electric dipole moments of underwater targets are obtained through calculation of a gradient positioning algorithm, a state equation and an observation equation of the underwater targets are established based on an underwater target electromagnetic field model, nonlinear state estimation of the underwater targets is carried out through a particle swarm filter algorithm, and dynamic tracking of the underwater targets is achieved. The method is suitable for the field of underwater security alert, and has good algorithm adaptability and high tracking precision.
Description
Technical Field
The invention relates to the technical field of underwater target detection, in particular to a method for positioning and tracking an underwater target by utilizing electromagnetic field characteristics of the underwater target.
Background
In order to realize the security protection of military requirements, important ports and important water areas of gulfs or seacoast in China, an underwater detection and positioning system needs to be built urgently to realize the normalized warning of underwater security.
Under water, the underwater safety warning device can detect and position through characteristics of a sound field, an electromagnetic field, optics and the like of an underwater target, and realizes underwater safety warning. For most underwater targets, the underwater targets are made of metal, the underwater targets are provided with fixed magnetic fields, induction magnetic fields can be generated under the action of geomagnetic fields, self-corrosion and corrosion protection systems among different metals can generate electrostatic fields and axial frequency electric fields, and detection, positioning and tracking can be realized by using electromagnetic field characteristic signals. At present, a method for positioning and tracking an underwater target based on electromagnetic field characteristics is lacked.
Disclosure of Invention
The invention aims to provide an underwater target tracking method based on electromagnetic field characteristic multi-information fusion, which is characterized in that a plurality of magnetic field sensors and electric field measuring electrodes are arranged in an array form, after three-direction coordinate position initial solutions, magnetic dipole moments and electric dipole moments of an underwater target are obtained through calculation of a gradient positioning algorithm, a state equation and an observation equation of the underwater target are established based on an underwater target electromagnetic field model, nonlinear state estimation of the underwater target is carried out by adopting a particle swarm filter algorithm, and dynamic tracking of the underwater target is realized.
The specific technical scheme of the invention provides an underwater target tracking method based on electromagnetic field characteristic multi-information fusion, which comprises the following steps:
and arranging a plurality of magnetic field sensors and electric field measuring electrodes, respectively acquiring magnetic field and electric field signals at different positions by using the magnetic field sensors and the electric field measuring electrodes, and analyzing and acquiring the characteristic quantities of the magnetic field and the electric field at the different positions to realize positioning and tracking of the underwater target.
Further, the method comprises the steps of:
step 1: acquiring magnetic field and electric field data of each position in a target area in real time by using a magnetic field sensor and an electric field measuring electrode, judging whether a measured abnormal value of a certain magnetic field sensor or the electric field measuring electrode is larger than a detection threshold value at any sampling moment, if so, judging that an underwater target appears, and executing the step 2, otherwise, continuing to execute the step 1;
step 2: performing associated spectrum analysis on the measured magnetic field and electric field data to obtain magnetic field and electric field characteristic components with different frequencies, and calculating by adopting a gradient positioning algorithm to obtain three-direction coordinate position initial solutions, magnetic dipole moments and electric dipole moments of the targets in the water;
and step 3: establishing an observation equation and a state equation of the underwater target based on an underwater target electromagnetic field mathematical model, dynamically solving a three-direction coordinate position of the underwater target by adopting a particle swarm filter algorithm by taking a measurement abnormal value of a magnetic field sensor or an electric field measuring electrode which is larger than a detection threshold as an observed quantity, and tracking the underwater target in real time;
and 4, step 4: and (3) judging whether the measurement abnormal value of at least 1 magnetic field sensor or electric field measurement electrode is larger than the detection threshold value, if so, repeating the step (3), otherwise, judging that the target in the water disappears, and returning to the step (1).
Preferably, in step 3, the established underwater target observation equation adopts an electromagnetic field observation model established by a magnetic dipole, an electric dipole, a time-harmonic magnetic dipole, and a time-harmonic electric dipole, and the step includes:
from the target motion state information, an observation equation is established according to the dipole model, i.e.
In the formula: b is0(k)、E0(k)、Bf(k) And Ef(k) Characteristic values of static, electrostatic, alternating magnetic and alternating electric fields for the object at the sensor, fB0(xT(k),yT(k),zT)、fE0(xT(k),yT(k),zT)、fBf(xT(k),yT(k),zT) And fEf(xT(k),yT(k),zT) Respectively, an electromagnetic field observation model established by a magnetic dipole, an electric dipole, a time harmonic magnetic dipole and a time harmonic electric dipole, and N (k) is noise of the measurement system.
Preferably, in step 3, a group of particles is respectively set for the static magnetic field, the electrostatic field, and the alternating electromagnetic field component acquired by the magnetic field sensing and electric field measuring electrodes in the particle swarm optimization algorithm to represent the target state, a posterior probability estimation of the target state is then obtained by calculating the weight of the particles, and a plurality of groups of electromagnetic field characteristic information are sorted according to the magnitude of the characteristic values, and the target state is represented by data with high accuracy and reliability, so as to obtain more accurate target tracking information by combining the judgment on the optimal particles.
The underwater target tracking method based on the electromagnetic field characteristic multi-information fusion provided by the invention has the following advantages:
(1) the invention constructs a brand-new observation model of electromagnetic field crosslinking, and by adopting the observation quantity and state quantity equation constructed by the invention, the information collected by a plurality of magnetic field sensors and electric field measuring electrodes can be effectively fused, and the mutual check and the deviation correction greatly improve the tracking precision;
(2) the non-linear state estimation of the underwater target is carried out by adopting a particle swarm filtering algorithm, the fusion of electromagnetic field characteristic information is realized, the track of the target can be accurately settled, and the tracking precision is high.
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FIG. 1 is a schematic diagram of the principle of an underwater target tracking method based on electromagnetic field characteristic multi-information fusion.
Detailed Description
The technical solution of the present invention will be further explained with reference to the accompanying drawings.
The underwater target tracking method based on electromagnetic field characteristic multi-information fusion comprises the following steps:
and arranging a plurality of magnetic field sensors and electric field measuring electrodes, respectively acquiring magnetic field and electric field signals at different positions by using the magnetic field sensors and the electric field measuring electrodes, and analyzing and acquiring the characteristic quantities of the magnetic field and the electric field at the different positions to realize positioning and tracking of the underwater target.
Further, the method comprises the steps of:
step 1: acquiring magnetic field and electric field data of each position in a target area in real time by using a magnetic field sensor and an electric field measuring electrode, judging whether a measured abnormal value of a certain magnetic field sensor or the electric field measuring electrode is larger than a detection threshold value at any sampling moment, if so, judging that an underwater target appears, and executing the step 2, otherwise, continuing to execute the step 1;
step 2: performing associated spectrum analysis on the measured magnetic field and electric field data to obtain magnetic field and electric field characteristic components with different frequencies, and calculating by adopting a gradient positioning algorithm to obtain three-direction coordinate position initial solutions, magnetic dipole moments and electric dipole moments of the targets in the water;
and step 3: establishing an observation equation and a state equation of the underwater target based on an underwater target electromagnetic field mathematical model, dynamically solving a three-direction coordinate position of the underwater target by adopting a particle swarm filter algorithm by taking a measurement abnormal value of a magnetic field sensor or an electric field measuring electrode which is larger than a detection threshold as an observed quantity, and tracking the underwater target in real time;
and 4, step 4: and (3) judging whether the measurement abnormal value of at least 1 magnetic field sensor or electric field measurement electrode is larger than the detection threshold value, if so, repeating the step (3), otherwise, judging that the target in the water disappears, and returning to the step (1).
The observation equation and the state equation of the underwater target in the step 3 are described as follows:
after the target magnetic moment, the electric dipole moment and the initial position are obtained through a positioning algorithm, the tracking process of the target can be modeled into a nonlinear state estimation process. Considering motion only in the horizontal direction, the equation of state is:
in the formula: x is the number ofTAnd yTIs the position of the target in the horizontal direction, vxTAnd vyTThe velocity of the target in the horizontal direction, w (k) the target motion system noise and Ts the sampling time interval.
The observation information is frequency components of the magnetic field and the electric field intensity acquired by the magnetic field sensor or the electric field measuring electrode, and consists of a plurality of groups of calculated abnormal measurement values which are larger than the detection threshold value. After the three-direction coordinate position initial solution, the magnetic dipole moment and the electric dipole moment of the target in the water are known, an observation equation can be established according to the dipole model by the motion state information of the target, namely
In the formula: b is0(k)、E0(k)、Bf(k) And Ef(k) Characteristic values of static, electrostatic, alternating magnetic and alternating electric fields for the object at the sensor, fB0(xT(k),yT(k),zT)、fE0(xT(k),yT(k),zT)、fBf(xT(k),yT(k),zT) And fEf(xT(k),yT(k),zT) Respectively, an electromagnetic field observation model established by a magnetic dipole, an electric dipole, a time harmonic magnetic dipole and a time harmonic electric dipole, and N (k) is noise of the measurement system.
The magnetic dipole model is described as follows:
assuming that the three-directional dipole moments of the magnetic dipoles are mx、myAnd mzThe three-component expression of the magnetic field strength H at a distance r (x, y, z) from the target in the water coordinate system is as follows:
the electric dipole model is described as follows:
the underwater target magnetic field is equivalent to a single horizontal electric dipole electric field, the marine environment is simplified to an air-seawater two-layer uniform conductive isotropic medium model, the electrode moments of the dipoles are Il respectively, and the three-component expression of the electric field intensity E at the position r (x, y, z) away from the target under an underwater target coordinate system is as follows:
the time harmonic dipole level sub-model adopts a modified direct current dipole method, namely, the dipole moment is modified according to the signal frequency, taking the time harmonic dipole as an example, the calculation formula is as follows:
Mexchange of electricity=MDirect current×(1-λ) (5)
Wherein λ is a correction factor corresponding to different signal frequencies f and longitudinal distances x, and the expression is
Wherein p isijThe (i, j ═ 0 to 5) is a constant, and can be obtained by fitting simulation data in advance.
For the above nonlinear state estimation problem, a particle filter algorithm (prior art in the field) is used for solving. The particle filtering method converts the state estimation of the target into the calculation of the posterior probability, and then obtains the optimal estimation of the target state through a preset estimation criterion.
Due to the diversity of the types of tracked targets, the contribution of each electromagnetic field characteristic to target detection will be different under different conditions; meanwhile, the accuracy and the reliability of the electromagnetic field value measured by each measuring unit are different under the influence of the signal-to-noise ratio. By considering the problems and combining the provided array detection scheme, the method constructs a brand-new cross-linked observation model, utilizes a particle wave algorithm to solve, and introduces multi-feature fusion into a particle filter algorithm: for the main components of static magnetic field, electrostatic field, alternating electromagnetic field and the like acquired by the measuring unit, a group of particles are respectively set to represent the target state, and the posterior probability estimation of the target state is obtained by calculating the weight of the particles, so that multi-feature information can be reserved, and the complexity of particle filtering calculation can be reduced; for a plurality of groups of electromagnetic field characteristic information acquired by different measuring units, sequencing is carried out according to the magnitude of characteristic values, and the data with high optimization accuracy and reliability represent the target state; and finally, more accurate target tracking information is obtained by combining the judgment of the optimal particles.
The present invention is not limited to the above embodiments, and those skilled in the art can implement the present invention in other various embodiments according to the disclosure of the embodiments and the drawings, and therefore, all designs that can be easily changed or modified by using the design structure and thought of the present invention fall within the protection scope of the present invention.
Claims (3)
1. An underwater target tracking method based on electromagnetic field feature multi-information fusion is characterized by comprising the following steps:
the method comprises the following steps of arranging a plurality of magnetic field sensors and electric field measuring electrodes in a target area, respectively acquiring magnetic field and electric field signals at different positions by using the magnetic field sensors and the electric field measuring electrodes, and positioning and tracking the target in water based on the characteristic quantities of the magnetic field and the electric field at the different positions, wherein the method comprises the following steps:
step 1: acquiring magnetic field and electric field data of each position in a target area in real time by using a magnetic field sensor and an electric field measuring electrode, judging whether a measured abnormal value of a certain magnetic field sensor or the electric field measuring electrode is larger than a detection threshold value at any sampling moment, if so, judging that an underwater target appears, and executing the step 2, otherwise, continuing to execute the step 1;
step 2: performing associated spectrum analysis on the measured magnetic field and electric field data to obtain magnetic field and electric field characteristic components with different frequencies, and calculating by adopting a gradient positioning algorithm to obtain three-direction coordinate position initial solutions, magnetic dipole moments and electric dipole moments of the targets in the water;
and step 3: establishing an observation equation and a state equation of the underwater target based on an underwater target electromagnetic field mathematical model, dynamically solving a three-direction coordinate position of the underwater target by adopting a particle swarm filter algorithm by taking a measurement abnormal value of a magnetic field sensor or an electric field measuring electrode which is larger than a detection threshold as an observed quantity, and tracking the underwater target in real time;
and 4, step 4: and (3) judging whether the measurement abnormal value of at least 1 magnetic field sensor or electric field measurement electrode is larger than the detection threshold value, if so, repeating the step (3), otherwise, judging that the target in the water disappears, and returning to the step (1).
2. The underwater target tracking method based on the multi-information fusion of the electromagnetic field features as claimed in claim 1, wherein the established underwater target observation equation in the step 3 adopts an electromagnetic field observation model established by a magnetic dipole, an electric dipole, a time-harmonic magnetic dipole and a time-harmonic electric dipole, and the step includes:
from the target motion state information, an observation equation is established according to the dipole model, i.e.
In the formula: b is0(k)、E0(k)、Bf(k) And Ef(k) Characteristic values of static, electrostatic, alternating magnetic and alternating electric fields for the object at the sensor, fB0(xT(k),yT(k),zT)、fE0(xT(k),yT(k),zT)、fBf(xT(k),yT(k),zT) And fEf(xT(k),yT(k),zT) Respectively, an electromagnetic field observation model established by a magnetic dipole, an electric dipole, a time harmonic magnetic dipole and a time harmonic electric dipole, and N (k) is noise of the measurement system.
3. The underwater target tracking method based on the multi-information fusion of the electromagnetic field features as claimed in claim 2, characterized in that in step 3, a group of particles is respectively set for the static magnetic field, the electrostatic field and the alternating electromagnetic field components acquired by the magnetic field sensing and electric field measuring electrodes in the particle swarm optimization algorithm to represent the target state, the posterior probability estimation of the target state is obtained by calculating the weight of the particles, and the target state is represented by a plurality of groups of electromagnetic field feature information according to the magnitude of the feature values, preferably by data with high accuracy and reliability, so as to obtain more accurate target tracking information by combining the judgment of the best particles.
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CN113158477A (en) * | 2021-04-28 | 2021-07-23 | 中国船舶重工集团公司第七一九研究所 | Multi-metal coupling corrosion simulation analysis method |
CN113702903A (en) * | 2021-09-22 | 2021-11-26 | 中船海洋探测技术研究院有限公司 | Array passive positioning and tracking method based on target underwater extremely-low-frequency vector electromagnetic field |
CN114114229A (en) * | 2021-11-10 | 2022-03-01 | 北京自动化控制设备研究所 | Underwater target detection method based on magnetostatic and axial frequency combined processing and aircraft |
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CN113702903B (en) * | 2021-09-22 | 2023-12-12 | 中船海洋探测技术研究院有限公司 | Array passive positioning tracking method based on target underwater very low frequency vector electromagnetic field |
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CN114705114A (en) * | 2022-03-02 | 2022-07-05 | 中国人民解放军海军工程大学 | Electric field measuring device positioning method, system, equipment and terminal |
CN114705114B (en) * | 2022-03-02 | 2023-03-14 | 中国人民解放军海军工程大学 | Electric field measuring device positioning method, system, equipment and terminal |
CN117665950A (en) * | 2024-01-31 | 2024-03-08 | 四川阳光上元科技有限公司 | Gas enrichment area detection method based on quantitative particles |
CN117665950B (en) * | 2024-01-31 | 2024-04-02 | 四川阳光上元科技有限公司 | Gas enrichment area detection method based on quantitative particles |
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