1b:I[76749,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"default"] 1c:I[3486,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"default"] 1d:I[41892,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"default"] 1e:I[17707,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"default"] 1f:I[66528,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"default"] 20:I[63176,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"default"] 21:I[87099,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"default"] 22:I[26200,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"Group"] 23:I[23365,["/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/df7e62179e4ae938.js","/_next/static/chunks/acf71181277ecf85.js","/_next/static/chunks/63561dcd578bd4db.js","/_next/static/chunks/5bf36002c846d2d8.js","/_next/static/chunks/b24fef6e58c9b2f5.js","/_next/static/chunks/ea1fda2cc52e974e.js"],"default"] 24:T4c1,In this paper, a weighted l₁-norm is proposed in a l₁-norm-based singular value decomposition (L1-SVD) algorithm, which can suppress spurious peaks and improve accuracy of direction of arrival (DOA) estimation for the low signal-to-noise (SNR) scenarios. The weighted matrix is determined by optimizing the orthogonality of subspace, and the weighted l₁-norm is used as the minimum objective function to increase the signal sparsity. Thereby, the weighted matrix makes the l₁-norm approximate the original l₀-norm. Simulated results of orthogonal frequency division multiplexing (OFDM) signal demonstrate that the proposed algorithm has s narrower main lobe and lower side lobe with the characteristics of fewer snapshots and low sensitivity of misestimated signals, which can improve the resolution and accuracy of DOA estimation. Specifically, the proposed method exhibits a better performance than other works for the low SNR scenarios. Outdoor experimental results of OFDM signals show that the proposed algorithm is superior to other methods with a narrower main lobe and lower side lobe, which can be used

Xian Zhang

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