Distributed batch estimation data fusion method of polynomial parameterized likelihood function

Abstract

The invention discloses a distributed batch estimation data fusion method of polynomial parameterized likelihood functions. The method comprises the following steps: firstly, setting a batch estimation update cycle according to the local radar sampling rate or the actual demands for data update, obtaining approximate local likelihood functions of particle samples in multiple sensors by using a particle filter algorithm, and then solving to obtain polynomial parameters of the local sensor through a least square approximation method, implementing communication interaction on the polynomial parameters between the multiple sensors, finally recovering to obtain the approximate likelihood functions of the multiple sensors approximate to the particle samples by using the polynomial parameters, and fusing the approximate likelihood functions of the multiple sensors by adopting a batch estimation fusion method. By adopting the distributed batch estimation data fusion method disclosed by the invention, the problem that the asynchronous data is difficult to fuse due to different sampling rate and initial deviation in an asynchronous sensor network can be effectively solved; compared with a method for directly transmitting the primary measurement data between multiple sensor nodes, the communication traffic for transmitting the polynomial parameters can be lower; and the application has a higher accuracy than that of a 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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