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)


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)
ISBN (Print)9781479974443
Publication statusPublished - 2015
Event5th Sensor Signal Processing for Defence 2015 - Edinburgh, United Kingdom
Duration: 9 Sept 201510 Sept 2015


Conference5th Sensor Signal Processing for Defence 2015
Abbreviated titleSSPD 2015
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Signal Processing
  • Instrumentation


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