Frequency Diverse Coprime Arrays With Coprime Frequency Offsets for Multitarget Localization
Frequency Diverse Coprime Arrays With Coprime Frequency Offsets for Multitarget Localization
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DOI：
10.1109/jstsp.2016.2627184
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发表时间：
2017-03-01
影响因子：
7.5
通讯作者：
Gini, Fulvio
中科院分区：
文献类型：
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作者：
Qin, Si;Zhang, Yimin D.;Gini, Fulvio
与传统相控阵雷达不同，频率分集阵列(FDA)雷达具有距离相关的波束方向图能力，在各种应用中具有很大的吸引力。FDA雷达的空间和距离分辨率从根本上受到阵列几何形状和频率偏移的限制。在本文中，我们通过引入一种结合互质阵列和互质频率偏移的基于稀疏性的多目标定位方法来克服这一局限性。建立对应于所有传感器和所使用频率的接收信号的协方差矩阵，以生成空频虚拟差协阵列。通过使用O(M+N)个天线和O(M+N)个频率，所提出的互质阵列能够在角域和距离域中定位高达O((MN)-N-2)个目标，分辨率为O(1/(MN))，其中M和N是互质整数。将波达方向和距离联合估计问题转化为二维稀疏重构问题，在贝叶斯压缩感知框架下进行求解。在多任务贝叶斯压缩感知算法的基础上，提出了一种计算复杂度较低的快速算法。仿真结果表明，该方法在波达方向距离分辨率、定位精度和可分辨目标个数等方面具有一定的优越性。
Different from conventional phased-array radars, the frequency diverse array (FDA) radar offers a range-dependent beampattern capability that is attractive in various applications. The spatial and range resolutions of an FDA radar are fundamentally limited by the array geometry and the frequency offset. In this paper, we overcome this limitation by introducing a novel sparsity-based multitarget localization approach incorporating both coprime arrays and coprime frequency offsets. The covariance matrix of the received signals corresponding to all sensors and employed frequencies is formulated to generate a space-frequency virtual difference coarrays. By using O(M + N) antennas and O(M + N) frequencies, the proposed coprime arrays with coprime frequency offsets enables the localization of up to O((MN2)-N-2) targets with a resolution of O(1/(MN)) in angle and range domains, where M and N are coprime integers. The joint direction-of-arrival (DOA) and range estimation is cast as a two-dimensional sparse reconstruction problem and is solved within the Bayesian compressive sensing framework. We also develop a fast algorithm with a lower computational complexity based on the multitask Bayesian compressive sensing approach. Simulations results demonstrate the superiority of the proposed approach in terms of DOA-range resolution, localization accuracy, and the number of resolvable targets.