CN-116203555-B - Multi-radar joint positioning method based on azimuth angle and Doppler speed

Abstract

The invention discloses a multi-radar combined positioning method based on azimuth angle and Doppler speed, which mainly solves the problems of poor positioning precision and insufficient multi-source data utilization caused by larger measurement error of the existing sensor. The method comprises the steps of aiming at a sea surface uniform motion target, constructing different filtering initial values and covariance matrixes according to different radar numbers by utilizing target direction finding results of 1-2 fixed passive radars and target Doppler speed measurement values of 1 fixed ground wave active radars, determining corresponding measurement equations and different filtering initial moments, filtering target states according to a uniform motion model, and outputting the filtering results as target positioning results. The method utilizes the measurement of the passive radar and the ground wave radar with two different systems, reduces the influence of a single measurement error on the positioning result, shortens the positioning time and improves the positioning precision.

Inventors

• GUAN JUN
• LU YING
• FANG SHANTING
• LU XIANG

Assignees

• 中国船舶集团有限公司第七二四研究所

Dates

Publication Date

20260512

Application Date

20221118

Claims (1)

1. 1. A multi-radar joint positioning method based on azimuth angle and Doppler speed is characterized in that: Step 1, aiming at a sea surface uniform motion target, the period of a radiation source with m fixed passive radar interception targets is as follows The measured target orientations are respectively Wherein m is 1 or 2, and a fixed ground wave active radar is arranged according to the signal period of the radiation source Measuring Doppler velocity of target The errors of (a) are all subject to Gaussian distribution, and the standard difference is that ; Step 2, calculating the initial value of the target state And covariance thereof Where diag (a) represents a matrix diagonal to vector a, in the context of m=2, Wherein Is utilized at time 1 The position estimation obtained by the triangulation is performed, Is utilized at time 2 The resulting position estimate, in the scenario where m=1, Wherein Is measured by passive radar using the previous N times The estimated direction of motion of the target at time t=n, And Is the measurement of the ground wave radar for the first N times Estimated target distance at time t=n And speed size , ; Step 3, by Measuring the target state vector according to the uniform motion model Filtering is performed in which Is the position of the x-axis, Is the x-axis velocity component and, Is the position of the y-axis and, Is the y-axis velocity component, the starting moment of the filtering is T, namely When m=2, the starting moment of the filtering The measurement vector is Nonlinear terms in the measurement equation: ; Wherein the method comprises the steps of And The positions of the two passive radars respectively, Is the position of the ground wave radar and measures noise Is Gaussian noise vector, the mean value is 0, and the variance matrix is When m=1, the filter starting time Measuring vector Nonlinear terms in the measurement equation: ; Measuring noise Gaussian vector, mean 0, variance matrix ; Step 4, filtering the result As a final output.

Description

Multi-radar joint positioning method based on azimuth angle and Doppler speed Technical Field The invention belongs to the technical field of radar data processing, and particularly relates to a multi-source sensor combined positioning method. Background The existing passive radar has a far reconnaissance range, can intercept a radiation source signal of an offshore beyond-view target, obtains a target azimuth through direction finding, but has larger direction finding error, so that the accuracy of a passive radar cooperative positioning result based on the direction finding is poor, and the positioning accuracy is further deteriorated along with the increase of the target distance. As a sensor different from the passive radar system, the ground wave radar has the capability of detecting an object beyond the visual range, but has poor distance and angle resolution and better doppler velocity measurement. With the development of military strike defense requirements, based on situation awareness capability of a single sensor, a multi-dimensional situation data cannot be provided and higher-quality target data cannot be provided, so that a technology based on multi-source sensor combined application needs to be studied, and particularly, target positioning is involved. Disclosure of Invention In order to solve the problems of poor positioning precision and insufficient utilization of multi-source data caused by larger measurement errors of the existing sensor, the invention provides a multi-radar combined positioning method based on azimuth angle and Doppler speed, aiming at sea surface uniform motion targets, and constructing different filtering initial values and covariance matrixes according to different radar numbers by utilizing target azimuth measurement of 1-2 fixed passive radars and target Doppler rate measurement of 1 fixed ground wave radars, determining corresponding measurement equations and different filtering initial moments, filtering a target state by adopting UKF, and outputting the filtering as a target positioning result. The technical scheme of the invention comprises the following steps: Step 1, aiming at a sea surface uniform motion target, m fixed passive radars intercept signals with the target radiation source period delta T, and the measured target orientations are respectively Wherein the value of m is 1 or2, and a fixed ground wave active radar measures the Doppler speed of the target according to the signal period delta T of the radiation sourceThe errors of (a) are all subject to Gaussian distribution, and the standard difference is that Step 2, calculating the initial value of the target stateAnd covariance P0＝diag([(3*vx,0*ΔT)2,(3*vx,0)2,(3*vy,0*ΔT)2,(3*vy,0)2]), thereof where diag (a) represents a matrix with vector a as diagonal element: in a scene where m=2,Wherein the method comprises the steps ofIs utilized at time 1The position estimation obtained by the triangulation is performed,Is utilized at time 2The resulting position estimate, in the scenario where m=1,Where α is the previous N measurements taken by the passive radarEstimated target motion direction at time t=n, r N and |v| are the previous N measurements taken by the ground wave radarThe estimated target distance r N and the estimated speed magnitude |v|atthe time t=N, wherein N is more than or equal to 3; step 3, by For measurement, the target state vector x t＝[xt;vx,t;yt;vy,t]T is filtered according to a uniform motion model, where x t is the x-axis position, v x, T is the x-axis velocity component, y t is the y-axis position, v y,t is the y-axis velocity component, the starting time of the filtering is T, i.e., t=t, t+1, where when m=2, the starting time of the filtering T is greater than or equal to 3, the measurement vector isNonlinear terms in the measurement equation: Wherein (x 1,y1) and (x 2,y2) are the positions of two passive radars respectively, (x 3,y3) is the position of the ground wave radar, and the noise is measured Is Gaussian noise vector, the mean value is 0, and the variance matrix isWhen m=1, the filtering starting time T is not less than n+1, and the measurement vector isNonlinear terms in the measurement equation: Measuring noise Is Gaussian vector, the mean value is 0, and the variance matrix is Step 4, filtering the resultAs a final output. The invention utilizes the measurement of two sensors with different systems of passive radar and ground wave radar, utilizes multi-source data, improves the positioning precision compared with a single system sensor, reduces the influence of single measurement error on the positioning precision by combined data processing, calculates a better filter initial value and shortens the time for effective positioning results. Drawings FIG. 1 is a flow diagram of an embodiment implementation. FIG. 2 is a plot of example positioning result distance error. FIG. 3 is a plot of example positioning result speed error. Detailed Description The process according to