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 language | English |
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Title of host publication | 2015 Sensor Signal Processing for Defence (SSPD) |
Publisher | IEEE |
ISBN (Print) | 9781479974443 |
DOIs | |
Publication status | Published - 2015 |
Event | 5th Sensor Signal Processing for Defence 2015 - Edinburgh, United Kingdom Duration: 9 Sept 2015 → 10 Sept 2015 |
Conference
Conference | 5th Sensor Signal Processing for Defence 2015 |
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Abbreviated title | SSPD 2015 |
Country/Territory | United Kingdom |
City | Edinburgh |
Period | 9/09/15 → 10/09/15 |
ASJC Scopus subject areas
- Signal Processing
- Instrumentation