Name
Abstract | ||
|---|---|---|
The generalized Radon-Fourier transform (GRFT) has been recently proposed for radar maneuvering weak target detection via long-time coherent integration. It is a likelihood ratio test (LRT) detector in a noisy background, but its computational burden can be extremely high due to the needed multi-dimensional search. This paper proposes a fast implementation of the GRFT based on an improved particle swarm optimization (PSO). This method uses the relation of the blind speed side lobe (BSSL) and target's main lobe to find the target's location in a much more efficient way, and the local convergence to BSSL problem can also be solved. Detailed numerical experiments are also provided to demonstrate the effectiveness and efficiency of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CIT.2012.113 | CIT |
Keywords | Field | DocType |
fourier transforms,radar maneuvering weak target detection,weak target detection,maneuvering target detection,detailed numerical experiment,target tracking,long-time coherent integration,likelihood ratio test detector,pso,particle swarm optimisation,generalized rft,generalized radon-fourier,computational burden,multidimensional search,efficient approach,improved particle swarm optimization,object detection,blind speed side lobe (bssl),radon transforms,generalized radon-fourier transform,main lobe,particle swarm optimization (pso),fast implementation,general radon-fourier transform (grft),blind speed side lobe,radar tracking,bssl problem,particle swarm optimization | Particle swarm optimization,Radar,Object detection,Mathematical optimization,Radar tracker,Likelihood-ratio test,Computer science,Main lobe,Side lobe,Local convergence | Conference |
ISBN | Citations | PageRank |
978-1-4673-4873-7 | 0 | 0.34 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lichang Qian | 1 | 53 | 4.74 |
| Jia Xu | 2 | 298 | 36.94 |
| Wenfeng Sun | 3 | 0 | 1.35 |
| Yingning Peng | 4 | 590 | 50.90 |