Sparse Scenario Imaging for Active Radar in the Forward-Looking Direction
Author(s) -
Jun Wang,
FengGang Yan,
Yinan Zhao,
Xiaolin Qiao
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/653208
Subject(s) - sparse approximation , radar , computer science , radar imaging , basis (linear algebra) , representation (politics) , compressed sensing , computer vision , joint (building) , doppler effect , sparse array , artificial intelligence , pulse repetition frequency , basis pursuit , algorithm , telecommunications , mathematics , engineering , physics , matching pursuit , astronomy , politics , architectural engineering , geometry , political science , law
The resolution of multiple targets at the same range cell but different angles in the forward-looking direction is of great trouble for active radar. Based on compressive sensing (CS) framework, a sparse scenario imaging approach using joint angle-Doppler representation basis is proposed, which employs multisensor and single-receiver channel hardware architecture. Firstly, the joint angle-Doppler representation basis is formulated using the Doppler dictionary, and then the radar returns during multiple pulse repetition periods are modeled as the measurements with respect to a stationary sparse target scenario via the joint representation basis; in the end, the image of sparse target scenario is recovered using the single-receiver echoes. Numerical experiments demonstrate that the proposed method can provide an image of the spatial sparse scenario at the same range for active radar in the forward-looking direction
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom