This paper considers a millimeter wave (mmWave) integrated sensing and communication (ISAC) system, where a base station (BS) equipped with a large number of antennas but a small number of radio-frequency (RF) chains emits pencillike narrow beams for persistent tracking of multiple moving targets. Under this model, the tracking lost issue arising from the misalignment between the pencil-like beams and the true target positions is inevitable, especially when the trajectories of the targets are complex, and the conventional Kalman filter-based scheme does not work well. To deal with this issue, we propose a Transformer-based mmWave multi-target tracking framework, namely m3TrackFormer, with a novel re-acquisition mechanism, such that even if the echo signals from some targets are too weak to extract sensing information, we are able to re-acquire their locations quickly with small beam sweeping overhead. Specifically, the proposed framework can operate in two modes of normal tracking and target re-acquisition during the tracking procedure, depending on whether the tracking lost occurs. When all targets are hit by the swept beams, the framework works in the Normal Tracking Mode (N-Mode) with a Transformer encoder-based Normal Tracking Network (N-Net) to accurately estimate the positions of these targets and predict the swept beams in the next time block. While the tracking lost happens, the framework will switch to the Re-Acquisition Mode (R-Mode) with a Transformer decoder-based Re-Acquisition Network (RNet) to adjust the beam sweeping strategy for getting back the lost targets and maintaining the tracking of the remaining targets. Thanks to the ability of global trajectory feature extraction, the m3TrackFormer can achieve high beam prediction accuracy and quickly re-acquire the lost targets, compared with other tracking methods.

翻译：本文研究一种毫米波一体化感知与通信系统，其中配备大量天线但射频链数量有限的基站发射笔状窄波束以实现对多个运动目标的持续跟踪。在此模型下，由于笔状波束与真实目标位置之间的失准所引发的跟踪丢失问题不可避免，尤其在目标轨迹复杂时，传统的基于卡尔曼滤波的方案难以有效应对。为解决该问题，我们提出一种基于Transformer的毫米波多目标跟踪框架——m3TrackFormer，其具备新颖的重捕获机制，即使某些目标的回波信号过弱而无法提取感知信息，仍能以较小的波束扫描开销快速重获其位置。具体而言，所提框架在跟踪过程中可根据是否发生跟踪丢失，在正常跟踪与目标重捕获两种模式下运行。当所有目标均被扫描波束命中时，框架工作于正常跟踪模式，通过基于Transformer编码器的正常跟踪网络精确估计这些目标的位置并预测下一时隙的扫描波束；而当发生跟踪丢失时，框架将切换至重捕获模式，利用基于Transformer解码器的重捕获网络调整波束扫描策略，以找回丢失目标并维持对剩余目标的跟踪。得益于全局轨迹特征提取能力，相较于其他跟踪方法，m3TrackFormer能够实现更高的波束预测精度并快速重获丢失目标。