Bearing-only-tracking pseudo-linear filtering method

Abstract

The invention relates to a bearing-only-tracking pseudo-linear filtering method. The method is performed as follows in each tracking period: acquiring measurement information from an observation radar, forming Gaussian distribution around a real target state and generating target state estimation under the condition of determining the current period to be an initial period; on the basis of the obtained measurement information, calculating state one-step prediction and a state prediction covariance by using a state equation; on the basis a quasi-linear measurement equation, calculating measurement one-step prediction and a measurement prediction covariance; acquiring an azimuth prediction value and a prediction measurement matrix based on the one-step prediction of the state and thus calculating a cross-covariance between the estimated state and the measurement; and calculating an updated state estimation and state estimation covariance to complete the target tracking of the current period. Therefore, the target tracking performance is improved effectively.

Description

technical field [0001] The invention relates to the technical field of space target tracking, in particular to a pure angle tracking pseudo-linear filtering method. Background technique [0002] Radar generally uses measurement information such as distance, azimuth, and Doppler velocity to locate and track targets. Pure angle tracking is a method of estimating the target's trajectory by only using a mobile sensor to measure the time-varying azimuth of the moving target, that is, the measurement information only has the azimuth as a parameter. Pure angle tracking usually requires the sensor platform to do maneuvers ahead of the target motion state, so that the target tracking trajectory can be observed. [0003] The main challenge of the angle-only tracking problem is the non-linear relationship between the azimuth measurement and the target state vector (target position and velocity). Therefore, the traditional Kalman filter is no longer suitable for the pure angle trackin...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to solve the problems of large state estimation deviation and poor tracking performance in the pure angle tracking method in the prior art.

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