Sensor registration using airlanes: Maximum likelihood solution

被引:0
|
作者
Ong, HT [1 ]
机构
[1] Boeing Co, Australian AEW&C RPT, Seattle, WA 98124 USA
关键词
sensor registration; sensor alignment; bias estimation; sensor bias; airlanes; flight plans; maximum likelihood estimation; performance bounds;
D O I
10.1117/12.502491
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this contribution, the maximum likelihood estimation of sensor registration parameters, such as range, azimuth and elevation biases in radar measurements. using airlane information is proposed and studied. The motivation for using airlane information for sensor registration is that it is freely available as a source of reference and it provides an alternative to conventional techniques that rely on synchronised and correctly associated measurements from two or more sensors. In the paper, the problem is first formulated in terms of a measurement model that is a nonlinear function of the unknown target state and sensor parameters, plus sensor noise. A probabilistic model of the target state is developed based on airlane information. The maximum likelihood and also maximum a posteriori solutions are given. The Cramer-Rao lower bound is derived and simulation results are presented for the case of estimating the biases in radar range, azimuth and elevation measurements. The accuracy of the proposed method is compared against the Cramer-Rao lower bound and that of an existing two-sensor alignment method. It is concluded that sensor registration using airlane information is a feasible alternative to existing techniques.
引用
收藏
页码:390 / 401
页数:12
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