Abstract
In this work, we consider the joint use of different passive sensors for the localization and tracking of human targets and small drones at short ranges, based on the parasitic exploitation of Wi-Fi signals. Two different sensors are considered in this paper: (i) Passive Bistatic Radar (PBR) that exploits the Wi-Fi Access Point (AP) as an illuminator of opportunity to perform uncooperative target detection and localization and (ii) Passive Source Location (PSL) that uses radio frequency (RF) transmissions from the target to passively localize it, assuming that it is equipped with Wi-Fi devices. First, we show that these techniques have complementary characteristics with respect to the considered surveillance applications that typically include targets with highly variable motion parameters. Therefore, an appropriate sensor fusion strategy is proposed, based on a modified version of the Interacting Multiple Model (IMM) tracking algorithm, in order to benefit from the information diversity provided by the two sensors. The performance of the proposed strategy is evaluated against both simulated and experimental data and compared to the performance of the single sensors. The results confirm that the joint exploitation of the considered sensors based on the proposed strategy largely improves the positioning accuracy, target motion recognition capability and continuity in target tracking.
Highlights
The detection, localization, tracking and classification of threats at short ranges have become the key requirements for surveillance systems intending to protect critical infrastructures, as well as private premises from intruders or hostile incursions, with an emphasis on unmanned aerial vehicles (UAV) [1,2,3,4]
The three USRP receiving channels were connected to three surveillance antennas, and the fourth channel was connected to the Access Point (AP), arranged to provide the dual-node system in Figure 3 operating with strategy #1 for the Passive Source Location (PSL); namely, an Angle of Arrival (AoA) and a TDoA were used
To capitalize on the sensor fusion for such targets, in this paper, we introduced a modified version of the Interacting Multiple Model (IMM) filter scheme aimed at fusing the measurements of two complementary positioning techniques based on Wi-Fi signals: Passive Bistatic Radar (PBR)
Summary
The detection, localization, tracking and classification of threats at short ranges have become the key requirements for surveillance systems intending to protect critical infrastructures, as well as private premises from intruders or hostile incursions, with an emphasis on unmanned aerial vehicles (UAV) [1,2,3,4] To this purpose, different sensing technologies might be employed, including audio, video, infrared (IR), radio frequency (RF) and radar sensors, a combination of two or more technologies being a preferable solution for improving the system performance and increasing its reliability. The proposed algorithm exploits the knowledge of the characteristics of the specific sensors providing measurements to properly modify the innovation process This improves their capability to select the best-suited motion model among those interacting within the IMM scheme.
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