A novel power-bearing approach and asymptotically optimum estimator for target motion analysis

The problem of target motion analysis (TMA) has been extensively investigated based on bearing-only (BO), Doppler-bearing (DB), and other measurement data. For radio frequency (RF) emitters, signal powers follow the well-known path loss law that can be utilized to aid localization and tracking of targets in BO-TMA, leading to the novel power-bearing (PB) approach as proposed in this paper. We begin our study with the standard “errorin-variable” (EIV) model to which the total least-squares (TLS) solution is known to be the maximum likelihood estimate (MLE), if errors are normal and i.i.d. (identically and independently distributed). However the EIV model arising from the TMA problem has a special structure in that its error matrix is diagonal. Although the TLS algorithm is not an MLE for such a class of EIV models, we will show that it is an asymptotic MLE under some mild condition. The results are then applied to develop the novel PB-TMA approach that is shown to be effective via a simulation example. Cramér-Rao lower bound (CRLB) is employed to demonstrate the performance improvements of PB-TMA over the BO-TMA. Our work shows the promise of PB-TMA for RF signals.