In this paper, a cooperative passive sensing system in millimeter-wave (mmWave) band for simultaneous device localization and target tracking, namely mmAlert, is proposed. Specifically, in uplink communication with at least two transmitters, the receiver receives the line-of-sight (LoS) signals and the scattered signals off a moving target, respectively. Based on the received signals of the sensing time intervals, when a passive target moves along one or multiple unknown trajectories, mmAlert could measure the angles-of-arrival (AoAs) and bistatic Doppler frequencies of the echoes from the sensing target, and then jointly estimate the locations of the transmitters and the trajectories of the target. Specifically, the transmitters' locations and the moving target's trajectories can be searched by minimizing the weighted mean squared error of the AoA and Doppler measurements. The optimal solution of the minimization problem is prohibitive due to the large number of variables. Hence, a low-complexity algorithm based on the alternating optimization is proposed, where the extended Kalman filter (EKF) is introduced to quickly shape the trajectories. The mmAlert is implemented in a 60GHz communication testbed. The experiment shows with the received signal spanning a single trajectory, the average localization error of the transmitters and average trajectory reconstruction error are 0.76 m and 0.29 m, respectively. The average errors are suppressed to 0.07 m and 0.2 m respectively, if the received signal spanning 50 trajectories is used. This justifies the benefit of trajectory diversity in localization and tracking.

翻译：本文提出了一种毫米波频段的协作无源感知系统——mmAlert，用于实现设备定位与目标跟踪的同步处理。具体而言，在上行链路通信中，接收端通过至少两个发射机分别接收视距信号和运动目标反射的散射信号。基于感知时间间隔内的接收信号，当无源目标沿一条或多条未知轨迹运动时，mmAlert能够测量来自感知目标的回波到达角与双基地多普勒频率，进而联合估计发射机位置与目标轨迹。具体地，通过最小化到达角与多普勒测量值的加权均方误差，可搜索发射机位置与运动目标轨迹。由于变量数量庞大，该最小化问题的最优解难以直接求解。为此，本文提出一种基于交替优化的低复杂度算法，并引入扩展卡尔曼滤波以快速成形轨迹。mmAlert系统已在60GHz通信测试平台上实现。实验表明：当接收信号覆盖单条轨迹时，发射机平均定位误差与目标轨迹重构平均误差分别为0.76米和0.29米；当使用覆盖50条轨迹的接收信号时，平均误差分别降至0.07米和0.2米。这验证了轨迹多样性在定位与跟踪中的优势。