The target motion analysis（TMA） for a moving scanning emitter with known fixed scan rate by a single observer using the time of interception（TOI） measurements only is investigated in this paper.By transforming the...The target motion analysis（TMA） for a moving scanning emitter with known fixed scan rate by a single observer using the time of interception（TOI） measurements only is investigated in this paper.By transforming the TOI of multiple scan cycles into the direction difference of arrival（DDOA） model,the observability analysis for the TMA problem is performed.Some necessary conditions for uniquely identifying the scanning emitter trajectory are obtained.This paper also proposes a weighted instrumental variable（WIV） estimator for the scanning emitter TMA,which does not require any initial solution guess and is closed-form and computationally attractive.More importantly,simulations show that the proposed algorithm can provide estimation mean square error close to the Cramer-Rao lower bound（CRLB） at moderate noise levels with significantly lower estimation bias than the conventional pseudo-linear least square（PLS） estimator.展开更多
基金co-supported by the Shanghai Aerospace Science and Technology Innovation Fund of China(No.SAST2015028)the Equipment Prophecy Fund of China(No.9140A21040115KG01001)
文摘The target motion analysis（TMA） for a moving scanning emitter with known fixed scan rate by a single observer using the time of interception（TOI） measurements only is investigated in this paper.By transforming the TOI of multiple scan cycles into the direction difference of arrival（DDOA） model,the observability analysis for the TMA problem is performed.Some necessary conditions for uniquely identifying the scanning emitter trajectory are obtained.This paper also proposes a weighted instrumental variable（WIV） estimator for the scanning emitter TMA,which does not require any initial solution guess and is closed-form and computationally attractive.More importantly,simulations show that the proposed algorithm can provide estimation mean square error close to the Cramer-Rao lower bound（CRLB） at moderate noise levels with significantly lower estimation bias than the conventional pseudo-linear least square（PLS） estimator.
