Joint Online Route Planning and Power Allocation for Multitarget Tracking in Airborne Radar Systems

Lu, Xiujuan; Kong, Lingjiang; Sun, Jun; Yuan, Ye

doi:10.1109/radarconf2043947.2020.9266327

Cited by 5 publications

(3 citation statements)

References 26 publications

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“…To start with, the following moderate assumptions are made to simplify the problem: (1) The emitted signal of each airborne radar node is a narrow-band signal. (2) The n-th airborne node is equipped with only a matched filter that correlates to its own transmitted waveform. (3) The time compression due to the Doppler shift is ignored.…”

Section: B Our Contributionsmentioning

confidence: 99%

“…It is indicated in [2][9] that the motion of each airborne radar node can also be built as a discrete time kinematic model, which consists of its location, kinematic velocity, and heading angle. Thus, the dynamic model of the n-th airborne radar node is expressed by:…”

Section: B Airborne Radar Dynamic Modelmentioning

confidence: 99%

“…In light of the aforementioned references, although there have been vast studies on flight route optimization and resource scheduling on demand, the above two aspects are always considered separately. The authors in [2] propose a joint online route planning and power allocation strategy for multitarget tracking in a monostatic airborne radar, whereas only the heading angle and transmit power are optimized, whose application is very limited. In addition, as stated previously, even though the transmit waveform selection and receiver path are jointly selected by a multistatic radar system in [9], the kinematic velocity, transmit power and dwell time of each airborne node are ignored.…”

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Joint Route Optimization and Multidimensional Resource Management Scheme for Airborne Radar Network in Target Tracking Application

Shi

Dai

Wang

et al. 2022

IEEE Systems Journal

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In this paper, we investigate the problem of joint route optimization and multi-dimensional resource management for airborne radar network in target tracking application. The mechanism of the proposed joint route optimization and multidimensional resource management (JRO-MDRM) scheme is to adopt the optimization technique to collaboratively design the flight route, transmit power, dwell time, waveform bandwidth, and pulse length of each airborne radar node subject to the system kinematic limitations and several resource budgets, with the aim of simultaneously enhancing the target tracking accuracy and low probability of intercept (LPI) performance of the overall system. The predicted Bayesian Cramér-Rao lower bound (BCRLB) and probability of intercept are calculated and employed as the metrics to gauge the target tracking performance and LPI performance, respectively. It is shown that the resulting optimization problem is non-linear and non-convex, and the corresponding working parameters are coupled in both objective functions, which is generally intractable. By incorporating the particle swarm optimization (PSO) and cyclic minimization approaches, an efficient four-step solution algorithm is proposed to deal with the above problem. Extensive numerical results are provided to demonstrate the correctness and advantages of our developed scheme compared with other existing benchmarks.Index Terms-Joint route optimization and multi-dimensional resource management (JRO-MDRM), airborne radar network, target tracking, Bayesian Cramér-Rao lower bound (BCRLB), low probability of intercept (LPI), particle swarm optimization (PSO). I. INTRODUCTION A. Background and Literature ReviewWith the significant superiorities over the static radar systems, the airborne radar network has received considerable interests in various applications, such as air defence, missile guidance, cooperative navigation, target localization, and so

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Section: B Our Contributionsmentioning

confidence: 99%

Section: B Airborne Radar Dynamic Modelmentioning

confidence: 99%

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