Maximum Likelihood Signal Parameter Estimation via Track before Detect

Murat Uney, Bernard Mulgrew, Daniel E Clark

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In this work, we consider the front-end processing for an active sensor. We are interested in estimating signal amplitude and noise power based on the outputs from filters that match transmitted waveforms at different ranges and bearing angles. These parameters identify the distributions in, for example, likelihood ratio tests used by detection algorithms and characterise the probability of detection and false alarm rates. Because they are observed through measurements induced by a (hidden) target process, the associated parameter likelihood has a time recursive structure which involves estimation of the target state based on the filter outputs. We use a track-before-detect scheme for maintaining a Bernoulli target model and updating the parameter likelihood. We use a maximum likelihood strategy and demonstrate the efficacy of the proposed approach with an example.

Original languageEnglish
Title of host publication2015 Sensor Signal Processing for Defence (SSPD)
PublisherIEEE
ISBN (Print)9781479974443
DOIs
Publication statusPublished - 2015
Event5th Sensor Signal Processing for Defence 2015 - Edinburgh, United Kingdom
Duration: 9 Sep 201510 Sep 2015

Conference

Conference5th Sensor Signal Processing for Defence 2015
Abbreviated titleSSPD 2015
CountryUnited Kingdom
CityEdinburgh
Period9/09/1510/09/15

ASJC Scopus subject areas

  • Signal Processing
  • Instrumentation

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  • Cite this

    Uney, M., Mulgrew, B., & Clark, D. E. (2015). Maximum Likelihood Signal Parameter Estimation via Track before Detect. In 2015 Sensor Signal Processing for Defence (SSPD) [7288511] IEEE. https://doi.org/10.1109/SSPD.2015.7288511