A Data Fusion Method for Distributed Batch Estimation of Polynomial Parameterized Likelihood Functions

Abstract

The invention discloses a distributed batch estimation data fusion method of a polynomial parameterized likelihood function. First, the batch estimation update cycle is set according to the sampling rate of the local radar or the actual demand for data update, and the particle samples in the multi-sensor are obtained by using the particle filter algorithm. The approximate local likelihood function, and then obtain the polynomial parameters of the local sensor by the least square approximation method, and communicate and interact these polynomial parameters among multiple sensors, and finally use the polynomial parameter recovery to obtain the approximate multi-sensor approximate likelihood function of the particle sample, And the batch estimation fusion method is used to fuse the approximate likelihood function of multiple sensors, which effectively solves the problem that the asynchronous data is difficult to fuse due to the difference in sampling rate and initial deviation in the asynchronous sensor network; compared with direct transmission between sensor nodes Raw measurements, the communication traffic of transmitting polynomial parameters is lower; the accuracy of the present application is higher compared to the posterior method.

Description

technical field [0001] The invention belongs to the technical field of multi-sensor data fusion, in particular to a distributed batch estimation data fusion technology of an asynchronous sensor network. Background technique [0002] With the increasing complexity of the modern battlefield environment, the urgent need for stealth and anti-stealth, confrontation and anti-confrontation, and the emergence of problems such as strong maneuverability, high clutter, low detection rate and high false alarm rate, using multi-sensor data fusion technology to obtain more Comprehensive, accurate and reliable environmental situation information has attracted more and more people's attention. Among them, the distributed estimation data fusion method has been greatly developed due to its advantages of low resource consumption, strong scalability, and good robustness, and has been widely used in many fields such as area monitoring, target tracking, and target positioning. [0003] Most of t...

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Problems solved by technology

[0004] In order to solve the above technical problems, the present invention proposes a distributed batch estimation data fusion method of polynomial parameterized likelihood function, and adopts the batch estimation fusion method to fuse the approximate likelihood functions of multiple sensors, effectively solving the problem of asynchronous sensor network The problem of difficult fusion of asynchronous data due to different sampling rates and initial deviations

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