COLD陣列近場(chǎng)源定位
發(fā)布時(shí)間:2019-02-26 08:59
【摘要】:利用特殊極化敏感陣列極化域的旋轉(zhuǎn)不變性,提出了一種基于交叉偶極子-磁環(huán)天線(xiàn)(COLD)陣的近場(chǎng)源閉式定位算法.與現(xiàn)有方法相比,該算法無(wú)需高維搜索和高階累積量運(yùn)算,也無(wú)需參數(shù)配對(duì),計(jì)算效率高;無(wú)需陣列具有對(duì)稱(chēng)結(jié)構(gòu),陣列孔徑利用率高.COLD陣方法無(wú)需高階項(xiàng)舍棄,與交叉偶極子陣方法相比,也不涉及接收模型的近似假設(shè),性能更優(yōu)越并可實(shí)現(xiàn)無(wú)偏定位.計(jì)算機(jī)仿真驗(yàn)證了所提算法的有效性.
[Abstract]:Based on the rotation invariance of polarization domain of special polarization sensitive array, a near-field closed source localization algorithm based on cross dipole-magnetic ring antenna (COLD) array is proposed. Compared with the existing methods, the algorithm does not require high-dimensional search and high-order cumulant operation, and also does not require parameter matching, so it has high computational efficiency. There is no need for the array to have symmetric structure and the array aperture utilization ratio is high. Compared with the cross dipole array method, the cold array method does not need to abandon the high-order terms and does not involve the approximate assumption of the receiving model, so the performance is better and the unbiased localization can be realized. The effectiveness of the proposed algorithm is verified by computer simulation.
【作者單位】: 北京理工大學(xué)信息與電子學(xué)院;
【基金】:國(guó)家自然科學(xué)基金資助項(xiàng)目(61072098,61072099)
【分類(lèi)號(hào)】:TN911.7
,
本文編號(hào):2430625
[Abstract]:Based on the rotation invariance of polarization domain of special polarization sensitive array, a near-field closed source localization algorithm based on cross dipole-magnetic ring antenna (COLD) array is proposed. Compared with the existing methods, the algorithm does not require high-dimensional search and high-order cumulant operation, and also does not require parameter matching, so it has high computational efficiency. There is no need for the array to have symmetric structure and the array aperture utilization ratio is high. Compared with the cross dipole array method, the cold array method does not need to abandon the high-order terms and does not involve the approximate assumption of the receiving model, so the performance is better and the unbiased localization can be realized. The effectiveness of the proposed algorithm is verified by computer simulation.
【作者單位】: 北京理工大學(xué)信息與電子學(xué)院;
【基金】:國(guó)家自然科學(xué)基金資助項(xiàng)目(61072098,61072099)
【分類(lèi)號(hào)】:TN911.7
,
本文編號(hào):2430625
本文鏈接:http://sikaile.net/kejilunwen/wltx/2430625.html
最近更新
教材專(zhuān)著