NNS distributed fusion estimator under multiple network constraints

For the distributed state fusion estimation problem of networked navigation system (NNS) with random communication delay and non-fixed packet loss rate under three network constraints, namely, node measurement gain attenuation, node energy limitation and system model uncertainty, the degree of node gain attenuation is described as a random variable with known statistical characteristics, and the system model uncertainty is described as a multiplicative colored color in the system matrix noise, the reduction of energy consumption of small cell network node is described as the reduction of the data transmission rate. To address the packet loss and delay issues, two distinct linear encoders are introduced at the target node and the adjacent node, respectively. In order to compensate the information loss caused by packet loss and transmission rate reduction, a function relationship between the non-fixed packet loss rate and the number of nodes transmitting information simultaneously is established. In order to solve the problem of information redundancy caused by communication delay, the target node linearly encodes multiple measurements from the same neighbor node in the same sampling period according to the time stamp. An augmented system model is established based on the new measurements added linearly at the end of the target node. The global fusion estimator form is obtained by utilizing the optimal matrix weighting approach, and the recursive form of the local unbiased estimation is generated by employing minimal variance. The sufficient conditions for the bounded covariance of the fusion estimation error and the suboptimal transmission rate are derived. Finally, an example is given to verify the effectiveness of the algorithm.