研究目的
To propose a 2D block (cid:2)1 (cid:2)0 norms homotopy sparse signal recovery algorithm (BL1L0) for ISAR imaging that utilizes block scatterers information of targets, aiming to achieve similar image quality as Bayesian-based algorithms but with faster computation speed.
研究成果
The proposed BL1L0 algorithm for ISAR imaging, based on a 2D block sparse signal recovery model, achieves similar image quality to Bayesian-based algorithms but with significantly faster computation speed, as verified by real data experiments.
研究不足
The assumption that scatterers can be approximated by small regular block scatterers may not hold for all targets, potentially limiting the algorithm's applicability to targets with irregular scatterer distributions.
1：Experimental Design and Method Selection:
The study extends the (cid:2)1 (cid:2)0 norms homotopy algorithm to a 2D signal model for ISAR imaging, assuming the scatterers can be approximated by small regular block scatterers.
2：Sample Selection and Data Sources:
Real data of a Yak-42 aircraft is used to demonstrate the performance of the proposed algorithm.
3：List of Experimental Equipment and Materials:
The radar system operates on the C band with a signal bandwidth of 400 MHz, and a pulse repetition frequency of 100 Hz.
4：Experimental Procedures and Operational Workflow:
The algorithm involves initialization, iteration with decreasing sequence of σ, gradient descent, and projection onto the feasible set.
5：Data Analysis Methods:
The performance is compared with PC-SBL algorithm in terms of image quality and computation time.
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