Presentation + Paper
2 May 2017 Passive ranging using signal intensity observations from a single fixed sensor
Author Affiliations +
Abstract
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.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kaipei Yang, Yaakov Bar-Shalom, Peter Willett, Z. Freund, and R. Ben-Dov "Passive ranging using signal intensity observations from a single fixed sensor", Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 1020004 (2 May 2017); https://doi.org/10.1117/12.2263793
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Sensors

Monte Carlo methods

Ranging

Motion estimation

Passive sensors

Error analysis

Motion measurement

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