Distributed batch estimation data fusion method of polynomial parameterized likelihood function

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