A passive ranging problem with elevation angle, azimuth angle and signal intensity measurements is presented and solved with a Maximum Likelihood (ML) estimator. The measurements used in the estimation are all obtained from a single passive sensor at a fixed location. The intensity measurement, which obeys the inverse square law w.r.t. the squared distance between the sensor and target has an unknown emitted energy that needs to be taken into account in the estimation problem. The Fisher Information Matrix (FIM) is investigated and used for observability testing. The simulation results from the scenarios considered prove the efficiency of the ML estimator.

Date Published: 2 May 2017
PDF: 7 pages
Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 1020004 (2 May 2017); doi: 10.1117/12.2263793

Published in SPIE Proceedings Vol. 10200:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI
Ivan Kadar, Editor(s)