Method for tracking weak maneuvering target angle through airborne digital array radar

Abstract

The invention proposes a method for tracking a weak maneuvering target angle through an airborne digital array radar. The method comprises the steps: taking a pitch angle error and an azimuth angle error as observation values, so as to respectively carry out the real-time measurement of curved line knee points; enabling a digital loop filter to employ a smaller loop equivalent noise bandwidth to tracking a target when there is a knee point. The method increases the angle error convergence rate of an angle tracking loop, reduces the filtering disturbance at the knee point, and maintains the continuity of tracking.

Description

technical field [0001] The invention belongs to the field of airborne digital array radar target tracking, and in particular relates to a method for airborne digital array radar to track weakly maneuvering target angles. Background technique [0002] In 1961, after R.E. Kalman proposed the Kalman filter algorithm, scholars proposed a large number of algorithms based on Kalman filter for the angle tracking of maneuvering targets by airborne digital array radar. Kalman filtering includes state equations and observation equations, in which the state transition matrix in the state equation is the modeling of the motion characteristics of the tracking target, and is also the key to determining whether the target can be accurately tracked. In general, due to the unpredictability of the target's motion model, the airborne digital array radar using the Kalman filter tracking algorithm cannot quickly reach the convergence state in the initial stage of tracking, and the tracking accur...

AI Technical Summary

Problems solved by technology

In general, due to the unpredictable motion model of the target, the airborne digital array radar using the Kalman filter tracking algorithm cannot quickly reach the convergence state in the initial stage of tracking, and the tracking accuracy is limited, and sometimes even filter divergence occurs

On the other hand, when entering the end stage of target tracking, that is, when the airborne digital array radar is close to the target, the angular position of the target seen from the digital array radar changes rapidly, and the state transition matrix in the traditional angle tracking algorithm based on Kalman filter The difference between the described target motion characteristics and the target's real motion trajectory model is intensified, and the tracking accuracy cannot be guaranteed, and the target tracking task cannot even be completed.

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