Title :
Radar echo signal detection with sparse representations
Author :
Gao, Dahua ; Liu, Danhua ; Feng, Youqian ; An, Qinli ; Yu, Fuping
Author_Institution :
Sch. of Sci., Air Force Eng. Univ., Xi´´an, China
Abstract :
Sparse decomposition can explore the most important or interesting features of a signal, thus it is very favorable in data compression, noise reduction, signal analysis, correction and other applications. In this paper, we propose a method of radar echo signal detection with sparse representations. In the proposed method, we first design a waveform-matched dictionary according to the a priori knowledge of the transmitted signal to sparsely represent the radar echo signal. The components in the dictionary have exactly the same waveform as the transmitted signal. With this dictionary, the echo signals of a given radar system have very sparse representation. Using the sparse representation based on the waveform-matched dictionary, the radar echo detection can bi achieved. Simulation results show that the proposed method is effective and has the high anti-noise ability.
Keywords :
radar cross-sections; radar signal processing; signal denoising; signal detection; signal representation; data compression; noise reduction; radar echo signal detection; signal analysis; signal correction; sparse decomposition; sparse signal representations; waveform-matched dictionary design; Approximation methods; Dictionaries; Matching pursuit algorithms; Noise; Radar detection; Sparse decomposition; linear frequency-modulated signal; overcomplete dictionary; radar echo signal;
Conference_Titel :
Signal Processing Systems (ICSPS), 2010 2nd International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-6892-8
Electronic_ISBN :
978-1-4244-6893-5
DOI :
10.1109/ICSPS.2010.5555846