Radio Frequency Signal Strength Based Multitarget Tracking With Robust Path Planning

The proliferation of technologically advanced and mobile devices poses risks to public safety security. These threats can be mitigated by systems equipped perform timely identification tracking their operators. In pursuit these capabilities, we propose an automated sensing platform designed specifically for multiple, radio frequency (RF) targets. There are a number challenges involved with multiple moving RF sources. We formulate the task as iterative state estimation path planning process, whereby sensor first estimates positions targets through observation environment then plans executes movement path. By developing model informed propagation theory, construct particle filter based estimator potential track using only signal strength observations. addition, technique rooted in uncertainty minimization constraints. Finally, validate proficiency proposed methods simulated experiments. Through analysis metrics localization performance show benefits our active techniques they apply demonstrate robustness method various environmental scenarios testing multitude realistic challenging experimental parameters (e.g., speed platform, targets, level signal-to-noise ratio (SNR)). results indicate that performs better than other state-of-the-art methods, significant improvements seen most difficult higher settings, is more often able localize less error position estimation. also computationally efficient scales well increasing