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FDA-MIMO radar for 3D localization: Virtual coprime planar array with unfolded coprime frequency offset framework and TRD-MUSIC algorithm
Digital Signal Processing ( IF 2.9 ) Pub Date : 2021-03-10 , DOI: 10.1016/j.dsp.2021.103017
Cheng Wang , Xiaofei Zhang , Jianfeng Li

The frequency diverse array multiple-input multiple-output (FDA-MIMO) radar can detect target range by exploiting a small frequency offset across the transmit sensors, which can be utilized to jointly estimate angle and range. Nevertheless, the detection performance is basically restricted by the array aperture and signal bandwidth. In this paper, we propose a joint optimization design scheme for FDA-MIMO radar, i.e., the virtual coprime planar array with ‘unfolded’ coprime frequency offsets (VCPA-UCFO) framework, for 3D localization without ambiguity. The VCPA-UCFO framework can significantly save sensors and physical space while remarkably extend array aperture and signal bandwidth, which brings about remarkably enhanced economic benefits and estimation performance. Additionally, we construct the 3D localization problem as 3D-MUSIC spatial spectrum function and transform the 3D total spectrum search of the conventional 3D-MUSIC algorithm into 1D local spectrum search by cooperating ESPRIT algorithm and twice reduce dimension MUSIC (TRD-MUSIC) algorithm. The TRD-MUSIC algorithm can significantly relieve computational burden but with no performance degradation. The CRBs are given as performance benchmark. The analysis and simulations have verified the effectiveness and advantages of VCPA-UCFO framework and TRD-MUSIC algorithm in system cost, localization accuracy, resolution and computational complexity.



中文翻译:

用于3D定位的FDA-MIMO雷达:具有展开的互质频偏框架和TRD-MUSIC算法的虚拟互质平面阵列

频率多样化阵列多输入多输出(FDA-MIMO)雷达可以通过利用跨发射传感器的小频率偏移来检测目标范围,该偏移可用于联合估计角度和范围。然而,检测性能基本上受阵列孔径和信号带宽的限制。在本文中,我们提出了一种针对FDA-MIMO雷达的联合优化设计方案,即具有“展开式”互质数频偏(VCPA-UCFO)框架的虚拟互质平面阵列,以便进行3D定位而不会产生歧义。VCPA-UCFO框架可以显着节省传感器和物理空间,同时显着扩展阵列孔径和信号带宽,从而带来显着增强的经济效益和评估性能。此外,我们将3D定位问题构造为3D-MUSIC空间频谱函数,并通过配合ESPRIT算法将常规3D-MUSIC算法的3D全谱搜索转换为1D局部谱搜索,并两次缩小维数MUSIC(TRD-MUSIC)算法。TRD-MUSIC算法可以显着减轻计算负担,但不会降低性能。CRB被作为性能基准。通过分析和仿真,验证了VCPA-UCFO框架和TRD-MUSIC算法在系统成本,定位精度,分辨率和计算复杂度方面的有效性和优势。TRD-MUSIC算法可以显着减轻计算负担,但不会降低性能。CRB被作为性能基准。通过分析和仿真,验证了VCPA-UCFO框架和TRD-MUSIC算法在系统成本,定位精度,分辨率和计算复杂度方面的有效性和优势。TRD-MUSIC算法可以显着减轻计算负担,但不会降低性能。CRB被作为性能基准。通过分析和仿真,验证了VCPA-UCFO框架和TRD-MUSIC算法在系统成本,定位精度,分辨率和计算复杂度方面的有效性和优势。

更新日期:2021-03-19
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