Array shape calibration using sources in unknown locations-a maximum likelihood approach
Array shape calibration using sources in unknown locations-a maximum likelihood approach
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DOI：
10.1109/29.45542
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发表时间：
1988-04
期刊：
影响因子：
--
通讯作者：
A. Weiss;B. Friedlander
中科院分区：
文献类型：
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作者：
A. Weiss;B. Friedlander
传感器位置的不确定性会严重降低测向系统的性能。一个精确的最大似然方法同时估计到达方向（DOA）和传感器的位置，以缓解这个问题。非分离源的情况，即，在同一频率单元中同时观察到的源。该算法是迭代的，并且在初始条件足够好的情况下收敛到似然函数的全局最大值。所选的数值例子表明，所提出的技术是能够纠正由于传感器位置的不确定性在DOA估计严重的错误。
Sensor location uncertainty can severely degrade the performance of direction finding systems. An exact maximum-likelihood method for simultaneously estimating directions of arrival (DOA) and sensor locations is developed to alleviate this problem. The case of nondisjoint sources, i.e., sources observed in the same frequency cell and at the same time, is emphasized. The algorithm is iterative and converges to the global maximum of the likelihood function is the initial conditions are good enough. Selected numerical examples demonstrate that the proposed technique is capable of correcting severe errors in the DOA estimates due to sensor location uncertainty.>