Name
Abstract | ||
|---|---|---|
The area of research dedicated to the design and optimisation of radar detection schemes is a constantly evolving held of study. This paper contributes to the held of parametric detection by utilising the Generalised Bessel Function K (GBK) distribution with parameter c = 2, (the Jakeman-Tough model), as a model for radar clutter in the design of an optimum detector. In order to apply standard statistical techniques in the design of our detector, a proof that the Jakeman-Tough model can represent an amplitude distribution of a spherically invariant random process is derived. Optimum detection, in the Neyman-Pearson sense, is then achieved by using the log-likelihood ratio test to implement the detector for the case when the input signal is known. |
Year | Venue | Keywords |
|---|---|---|
1996 | ISSPA 96 - FOURTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, PROCEEDINGS, VOLS 1 AND 2 | probability density function,testing,detectors,random processes,log likelihood ratio |
Field | DocType | Citations |
Continuous-wave radar,Radar engineering details,Computer science,Artificial intelligence,Detector,Space-time adaptive processing,Pulse-Doppler radar,Pattern recognition,Clutter,Algorithm,Bistatic radar,Constant false alarm rate,Statistics | Conference | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. C. Smith | 1 | 0 | 0.34 |
| M. Martin | 2 | 10 | 3.08 |
| D. Robert Iskander | 3 | 104 | 23.65 |