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Bernoulli Filter for Track-Before-Detect: Swerling-1 Target in K-distributed Clutter
- Source :
- 2019 International Radar Conference (RADAR).
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- In this paper, we investigate the problem of detecting and tracking small targets in sea clutter using the Bernoulli Track-Before-Detect filter. This filter is an optimal recursive Bayesian detector / estimator to determine the state of a single target and its presence in noise. Typically, clutter amplitude fluctuations are modelled using the Rayleigh distribution. This assumption, however, is not valid in the maritime domain, where sea-clutter is often spikier with a longer distribution tail. In this work, we develop the Bernoulli filter for a compound Gaussian clutter model with thermal noise and model the target with a Swerling 1 fluctuation. To demonstrate the performance improvement, we model the texture as a gamma distribution, giving an overall K plus noise distribution for the clutter plus noise. The detection and tracking improvement is then demonstrated using Monte Carlo simulation.
- Subjects :
- 020301 aerospace & aeronautics
Radar tracker
Rayleigh distribution
Computer science
020206 networking & telecommunications
02 engineering and technology
Filter (signal processing)
Track-before-detect
Noise (electronics)
Bernoulli's principle
0203 mechanical engineering
Computer Science::Computer Vision and Pattern Recognition
0202 electrical engineering, electronic engineering, information engineering
Gamma distribution
Clutter
Algorithm
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2019 International Radar Conference (RADAR)
- Accession number :
- edsair.doi...........6757259f3b3a89086a83ae10527f7f7c