Arbitrary linear constraint tracking method for simultaneously estimating target state and trajectory parameter

Abstract

The invention relates to an arbitrary linear constraint tracking method for simultaneously estimating a target state and a trajectory parameter. The method comprises: acquiring target position measurement information from an observation radar; carrying out augmentation on a state vector by using a slope and a y-axis intercept parameter component to obtain an augmented state vector and augmented state equation, and constructing a pseudo-measurement description constraint relationship; processing measurement information, carrying out nonlinear filtering by using the processed measurement, the augmented state equation and pseudo-measurement, and updating the state estimation and state estimation covariance to realize target tracking. According to the provided method, the trajectory parametersare augmented to the state vector and the shape feature information in the target motion trajectory is utilized reasonably, so that the information wasting is avoided and the estimation precision isimproved; because of sequential processing of radar measurement and pseudo-measurement, the computational burden is reduced; and the filtering result contains the trajectory parameter estimation result, so that the subsequent information processing is performed smoothly.

Description

technical field [0001] The invention relates to the technical field of space target tracking, in particular to an arbitrary straight line constraint tracking method for simultaneously estimating target state and trajectory parameters. Background technique [0002] Constrained state estimation is a method for estimating the state of the target state under the condition of equality or inequality constraints. In many actual target tracking scenarios, the trajectory of the target is not completely determined by the speed of the target itself, but is affected or restricted by its physical environment or its own motion characteristics, which is not an unconstrained free movement. Reasonable use of the constraint information contained in these actual scenes can effectively improve the estimation performance and filtering accuracy. [0003] In the actual tracking scene, there is such a constraint, which is derived from the common shape characteristics of all straight-line trajector...

AI Technical Summary

Problems solved by technology

However, the specific information about its navigation route is generally difficult to obtain accurately, and the real trajectory of the target may not completely coincide with the route.

Therefore, in this type of constrained target tracking, the available constrained prior information is only the shape feature of the target trajectory, which cannot be described by traditional constrained modeling methods.

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