# Online Sparse DOA Estimation Based on Sub-Aperture Recursive LASSO for TDM-MIMO Radar
); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.H.) [PERSON]  
1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengda 611731, China; [PERSON]RESS] (J.L. ); [EMAIL_ADDRESS] (J.Y. ); [EMAIL_ADDRESS] (D.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.H.) [PERSON]  
1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengda 611731, China; [PERSON]RESS] (J.L. ); [EMAIL_ADDRESS] (J.Y. ); [EMAIL_ADDRESS] (D.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.H.) [PERSON]  
1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengda 611731, China; [PERSON]ADDRESS] (J.L. ); [EMAIL_ADDRESS] (J.Y. ); [EMAIL_ADDRESS] (D.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.H.) [PERSON]  
1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengda 6111731, China; [PERSON]RESS] (J.L. ); [EMAIL_ADDRESS] (J.Y. ); [EMAIL_ADDRESS] (D.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.H.) [PERSON]  
1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengda 6111731, China; [PERSON]RESS] (J.L. ); [EMAIL_ADDRESS] (J.Y. ); [EMAIL_ADDRESS] (D.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.H.) [PERSON]  
1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengda 611731, China; [PERSON]RESS] (J.L. ); [EMAIL_ADDRESS] (J.Y. ); [EMAIL_ADDRESS] (D.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.H.) [PERSON]  
1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengda 611731, China; [PERSON]RESS] (J.L. ); [EMAIL_ADDRESS] (J.Y. ); [EMAIL_ADDRESS] (D.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (Y.H.) [PERSON]  
1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengda 611731, China; [EMAIL_ADDRESS] (J.L. the number of channels, which is very uneconomical. Many methods have been proposed to effectively improve the DOA resolution of MIMO radar [13; 14; 15; 16; 17; 18; 19; 20]. Based on the rotational invariance property of spatially correlated matrix signal subspaces, the estimation of signal parameters via the invariance technique (ESPRIT) algorithm was proposed to improve the DOA estimation accuracy of MIMO radar [13; 14]. The parallel factor analysis (PARAFAC) algorithm was proposed to improve the multitarget resolution [15]. A dimensionality-reducing Capon method has been proposed for the DOA estimation of monostatic MIMO radars [17], and this method reduces the dimensions of the MIMO radar sub-aperture through a dimensionality-reducing transformation, thereby accelerating the Capon algorithm. In [1; 21], the iterative adaptive approach (IAA) was introduced for MIMO radar imaging, and it was shown that the IAA can work with few or even a single snapshot, and can provide a higher azimuthal signal source localization accuracy. However, this method suffers from a high computational complexity due to its high dimensional matrix inverse computation per iteration. The sparse representation (SR) has been used in an estimation method that contains DOA estimation for colocated TDM-MIMO radars [19]. The least absolute shrinkage and selection operator (LASSO) method [22] is an efficient tool in the fields of application of sparse linear regression [23; 24].