Multidimensional Parameter Estimation Method Based on Sparse Iteration in FDA-MIMO Radar
Gong Pengcheng①③* Liu Gang② Huang He② Wang Wenqin③
①(School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China) ②(CETC Key Laboratory of Electromagnetic Domain Operation, No.29 Research Institute of CETC, Chengdu 610036, China) ③(School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)
Abstract To accurately identify the range of each target, traditional Multiple-Input Multiple-Output (MIMO) radar techniques not only require designing a shift matrix to describe different range bins but also a large number of snapshots.To alleviate this problem, a multidimensional parameter estimation method based on sparse iteration is proposed for a MIMO radar with Frequency Diverse Array (FDA).The FDA-MIMO radar uses small frequency increments across the array elements, and its transmit steering vector is a function of both range and angle.On the basis of the feature of the FDA-MIMO radar, we consider a weighted lq (0 < q ≤ 1) minimization problem that is solved using a sparse iterative algorithm.Finally, the target parameters (the amplitude, range, and angle) are obtained using a single snapshot.Moreover, numerical simulations are used to demonstrate the superior performance of the proposed method compared with those of DAS, IAA, and IAA-R.
Fund: The National Natural Science Foundation of China (61601178), China Postdoctoral Science Foundation (2016M600729), The Doctoral Starting up Foundation (BSQD14032)
Cite this article:
Gong Pengcheng,Liu Gang,Huang He et al. Multidimensional Parameter Estimation Method Based on Sparse Iteration in FDA-MIMO Radar[J]. JOURNAL OF RADARS, 2018, 7(2): 194-201.
2018, Vol. 7 
