Back to Search
Start Over
ℓ p -Based complex approximate message passing with application to sparse stepped frequency radar
- Source :
- Signal Processing. 134:249-260
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- Compressed sensing exploits the sparsity of the signal to reduce the sampling rate while keeping the resolution fixed, and has been widely used. In this paper we propose a new algorithm called adaptive p-CAMP and show its application in the sparse stepped frequency radar signal processing. Our algorithm is inspired by the complex approximate message passing algorithm (CAMP) that solves complex-valued LASSO. The following properties of the proposed algorithm make it superior to existing algorithms: (1) All the parameters of the algorithm are tuned dynamically and optimally. The algorithm does not require any information about the signal and is still capable of tuning the parameters as well as an oracle that has all the signal information. (2) Adaptive p-CAMP is designed to solve the complex-valued p-regularized least squares for 0p1. Hence, it can outperform CAMP. The performance of the proposed algorithm is verified by simulations and the data collected by a real radar system. HighlightsA new compressed sensing algorithm called adaptive lp-CAMP is proposed.The proposed algorithm can be applied to the sparse stepped frequency radar signal processing.The performance of the proposed algorithm is verified by simulations and real data.
- Subjects :
- Mathematical optimization
Computer science
Message passing
0211 other engineering and technologies
020206 networking & telecommunications
02 engineering and technology
Least squares
Signal
Oracle
law.invention
Compressed sensing
Sampling (signal processing)
Lasso (statistics)
Control and Systems Engineering
law
Ramer–Douglas–Peucker algorithm
Signal Processing
0202 electrical engineering, electronic engineering, information engineering
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering
Radar
Algorithm
Software
021101 geological & geomatics engineering
Subjects
Details
- ISSN :
- 01651684
- Volume :
- 134
- Database :
- OpenAIRE
- Journal :
- Signal Processing
- Accession number :
- edsair.doi...........847ac14ae0b174333ccfa97a7abc677e