@article{(Open Science Index):https://publications.waset.org/pdf/10012711,
	  title     = {Statically Fused Unbiased Converted Measurements Kalman Filter},
	  author    = {Zhengkun Guo and  Yanbin Li and  Wenqing Wang and  Bo Zou},
	  country	= {},
	  institution	= {},
	  abstract     = {Active radar and sonar systems often report Doppler measurements in addition to the position measurements such as range and bearing. The tracker can perform better by making full use of the Doppler measurements. However, due to the high nonlinearity of the Doppler measurements with respect to the target state in the Cartesian coordinate systems, those measurements are not always fully exploited. This paper mainly focuses on dealing with the Doppler measurements as well as the position measurements in Polar coordinates. The Statically Fused Converted Position and Doppler Measurements Kalman Filter (SF-CMKF) with additive debiased measurement conversion has been presented. However, the exact compensation for the bias of the measurement conversion are multiplicative and depend on the statistics of the cosine of the angle measurement errors. As a result, the consistency and performance of the SF-CMKF may be suboptimal in the large angle error situations. In this paper, the multiplicative unbiased position and Doppler measurement conversion for two-dimensional (Polar-to-Cartesian) tracking are derived, and the SF-CMKF is improved by using those conversion. Monte Carlo simulations are presented to demonstrate the statistic consistency of the multiplicative unbiased conversion and the superior performance of the modified SF-CMKF (SF-UCMKF).},
	    journal   = {International Journal of Computer and Systems Engineering},
	  volume    = {16},
	  number    = {10},
	  year      = {2022},
	  pages     = {431 - 436},
	  ee        = {https://publications.waset.org/pdf/10012711},
	  url   	= {https://publications.waset.org/vol/190},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 190, 2022},
	}