scholarly journals Modified Extended Kalman Filtering for Tracking with Insufficient and Intermittent Observations

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Pengpeng Chen ◽  
Honglu Ma ◽  
Shouwan Gao ◽  
Yan Huang

This paper is concerned with the Kalman filtering problem for tracking a single target on the fixed-topology wireless sensor networks (WSNs). Both the insufficient anchor coverage and the packet dropouts have been taken into consideration in the filter design. The resulting tracking system is modeled as a multichannel nonlinear system with multiplicative noise. Noting that the channels may be correlated with each other, we use a general matrix to express the multiplicative noise. Then, a modified extended Kalman filtering algorithm is presented based on the obtained model to achieve high tracking accuracy. In particular, we evaluate the effect of various parameters on the tracking performance through simulation studies.

2014 ◽  
Vol 596 ◽  
pp. 494-497
Author(s):  
Yong Sun ◽  
Jun Wei Zhao

The Extended Kalman Filter methods were widely used in the estimation of tracing situation in military fields. In this paper, we proposed a method of using multiple iteration of the observation and covariance matrix in the measuring equations during the tracking process in bistatic sonar system. Therefore the iterating extended kalman filtering (IEKF) algorithm was emerged at this situation. The simulation results show that the proposed tracing algorithm exhibits higher accuracy compared with the EKF algorithm. This new method can take full application of the measured information to improved the tracing accuracy in the whole controlled area. Keywords: bistatic sonar; tracing accuracy; IEKF algorithm; target moving analysis


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