系统工程与电子技术
繫統工程與電子技術
계통공정여전자기술
SYSTEMS ENGINEERING AND ELECTRONICS
2014年
9期
1696-1701
,共6页
景小荣%杨洋%张祖凡%陈前斌
景小榮%楊洋%張祖凡%陳前斌
경소영%양양%장조범%진전빈
均匀线阵%混合信号%波达方向估计%互耦自校正
均勻線陣%混閤信號%波達方嚮估計%互耦自校正
균균선진%혼합신호%파체방향고계%호우자교정
uniform linear array (ULA)%mixed signals%direction-of-arrival (DOA)estimation%mutual coupling self-calibration
针对均匀线阵(uniform linear array,ULA)互耦条件下混合信源的波达方向(direction of arrival, DOA)估计问题,基于联合对角化算法,提出了一种基于3步实现的 DOA 与互耦系数估计新算法。首先利用互耦矩阵的 Toeplitz 结构实现混合信源中独立信源的 DOA 及互耦系数的粗估计;然后结合斜投影及前后向空间平滑,实现混合信源 DOA 估计;最后以广义空间特征矩阵及混合信源 DOA 估计值为基础,提出一种非子空间类互耦系数自校正方法。计算机仿真结果表明,与同类算法相比,所提算法无论在 DOA 及互耦系数估计精度、还是在DOA 估计成功率方面,均具有明显的优势,且对于高斯背景噪声具有普适性。
針對均勻線陣(uniform linear array,ULA)互耦條件下混閤信源的波達方嚮(direction of arrival, DOA)估計問題,基于聯閤對角化算法,提齣瞭一種基于3步實現的 DOA 與互耦繫數估計新算法。首先利用互耦矩陣的 Toeplitz 結構實現混閤信源中獨立信源的 DOA 及互耦繫數的粗估計;然後結閤斜投影及前後嚮空間平滑,實現混閤信源 DOA 估計;最後以廣義空間特徵矩陣及混閤信源 DOA 估計值為基礎,提齣一種非子空間類互耦繫數自校正方法。計算機倣真結果錶明,與同類算法相比,所提算法無論在 DOA 及互耦繫數估計精度、還是在DOA 估計成功率方麵,均具有明顯的優勢,且對于高斯揹景譟聲具有普適性。
침대균균선진(uniform linear array,ULA)호우조건하혼합신원적파체방향(direction of arrival, DOA)고계문제,기우연합대각화산법,제출료일충기우3보실현적 DOA 여호우계수고계신산법。수선이용호우구진적 Toeplitz 결구실현혼합신원중독립신원적 DOA 급호우계수적조고계;연후결합사투영급전후향공간평활,실현혼합신원 DOA 고계;최후이엄의공간특정구진급혼합신원 DOA 고계치위기출,제출일충비자공간류호우계수자교정방법。계산궤방진결과표명,여동류산법상비,소제산법무론재 DOA 급호우계수고계정도、환시재DOA 고계성공솔방면,균구유명현적우세,차대우고사배경조성구유보괄성。
Based on the joint approximative diagonalization of eigen matrix,a novel algorithm which in-cludes three steps is proposed to estimate the direction-of-arrival (DOA)of mixed signals and the mutual cou-pling coefficient of the uniform linear array (ULA)in presence of the mutual coupling error.Utilizing the To-eplitz structure of the mutual coupling matrix,the coarse estimates of the DOAs of the uncorrelated signals among the mixed signals and mutual coupling coefficients are firstly obtained.Then the DOA estimates of the mixed signals are obtained based on the combination of the oblique projection with forward and backward spatial smoothing methods.Finally,a non-subspace method for mutual coupling self-calibration is presented by utili-zing the estimates of the generalized spatial feature matrix and the estimated mixed signal DOAs.The computer simulation results indicate that the proposed algorithm has much better performance in DOAs and mutual cou-pling coefficient estimation and the successful rate compared with the similar algorithm,and it is also universal for Gaussian background noises.