Plot association allocation method based on quasi-Newton method

Abstract

The invention provides a plot correlation distribution method based on a quasi-Newton method. The plot correlation distribution method comprises the following steps: firstly, giving a displacement calculation formula of a flight path under the influence of tangential and normal accelerations on the basis of a uniform acceleration model; secondly, decomposing a displacement change formula to reducecalculation complexity, and establishing an iterative model for solving tangential acceleration and normal acceleration based on a quasi-Newton method; constructing an energy formula again to evaluate the influence degrees determined by different trace point distribution schemes; and finally, giving out a route cross avoidance rule and a minimum energy rule, optimizing a plot allocation scheme, and preventing a plot allocation error.

Description

technical field [0001] The invention belongs to the technical field of radar data processing. Background technique [0002] The correlation between point track and track is the key problem of multi-sensor tracking, which largely determines the stability and correctness of track target, the accuracy and reliability of track filter state, and then affects the application support ability of track target data. At present, the main data association methods include nearest neighbor method, global optimal method, probabilistic data association (PDA), interactive multi-model, joint probability (JPDA), neural network and other methods. The association method based on probability theory and neural network ignores track For the dynamic characteristics of target navigation, the association method based on the probabilistic model needs to calculate the degree of membership of the track, which has high complexity and poor adaptability. Methods such as interactive multi-model and neural ne...

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Problems solved by technology

At present, the main data association methods include nearest neighbor method, global optimal method, probabilistic data association (PDA), interactive multi-model, joint probability (JPDA), neural network and other methods. The association method based on probability theory and neural network ignores track Due to the dynamic characteristics of target navigation, the association method based on the probability model needs to calculate the degree of membership of the track, which has high complexity and poor adaptability. It is difficult to balance the contradiction between the model complexity and the amount of calculation by methods such as interactive multi-model and neural network.

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