Adaptive Beam Scheduling for Cooperative Phased Array Radars With High-Precision Pencil-Beam

• Published in: IEEE transactions on aerospace and electronic systems Vol. 59; no. 6; pp. 1 - 14
• Main Authors: Deng, Anbang, Pektas, Fatih, Kumru, Firat, Tharmarasa, Ratnasingham, Efe, Murat, Kirubarajan, Thiagalingam
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Beam scheduler; Cramer-Rao bounds; Genetic algorithms; Lower bounds; Maneuvering targets; Military applications; Mixed integer; narrow beam width; Optimization; phased array radar; Phased arrays; posterior cramér-rao lower bound; Radar; Radar arrays; Radar tracking; Resource allocation; Resource management; Scheduling; Target tracking; Task analysis; Tracking
• ISSN: 0018-9251; 1557-9603
• DOI: 10.1109/TAES.2023.3308549

Phased array radar (PAR) has attracted considerable attention in civil and military applications due to its capability of performing multiple tasks such as surveillance, tracking and weapon engagement simultaneously. To make better use of limited radar resources and to offer best operating performance, an efficient resource allocation strategy is necessary. Traditional PAR schedulers are inefficient in using pencil-beams with super narrow beamwidth to cover areas of interest especially in cases of maneuvering targets with high motion uncertainty which results in missed detection. In order to utilize the limited time and the energy resources required for PAR with pencil beams, it is necessary to provide an efficient beam scheduling algorithm. However, existing works often assume that a beam can cover the entire area of interest thus the problem of scheduling small-beamwidth pencil-beam to perform search and track (SAT) efficiently is barely discussed or addressed in literature. In this paper, the problems of tracking with pencil-beam and its beam scheduling optimization are addressed. Three beam scheduling strategies, fixed linear wipe, open-loop linear wipe that uses hierarchical genetic algorithm (HGA), and expected posterior Cramér-Rao lower bound (EPCRLB) based optimal solution, are proposed to solve the mixed integer nonlinear problem (MINP). To handle the partially covered target existence area by pencil-beam, a new concept of predicted expected posterior Cramér-Rao lower bound (P-EPCRLB) is proposed and used as the main optimization criterion for the scheduling strategy. Numerical results demonstrate the superior performance of the proposed EPCRLB based optimal solution strategy and its effectiveness as a proposed solution.