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LPI optimization framework for search radar network based on information fusion
- Source :
- Aerospace Science and Technology. 67:206-214
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- This paper addresses the problem of joint power management and radar assignment to detect multiple targets in surveillance region for a distributed mono-static radar network while a low probability of interception (LPI) has been attained. Based on detection probabilities and target location estimates, the targeted problem is formulated as a combinatorial non-convex optimization problem which needs exhaustive search through all assignment schemes to reach optimal solution. Due to NP-hardness and non-convexity of the problem, some relaxations are proposed to transform the problem to a more tractable form. The main problem can be considered from two viewpoints, without information fusion and with information fusion. As another relaxation, we separated power allocation from radar assignments through two sub-problems in which first, the optimum power allocation is obtained for each assignment scheme and second, the target assignment schemes are selected based on the allocated powers. Simulation results show that our proposed algorithms not only guarantee detection performances but also considerably improve LPI specification in comparison with benchmark algorithms.
- Subjects :
- Power management
Mathematical optimization
Engineering
Optimization problem
Quadratic assignment problem
business.industry
010401 analytical chemistry
Aerospace Engineering
Brute-force search
020206 networking & telecommunications
02 engineering and technology
01 natural sciences
0104 chemical sciences
law.invention
law
0202 electrical engineering, electronic engineering, information engineering
Benchmark (computing)
Relaxation (approximation)
Radar
business
Weapon target assignment problem
Subjects
Details
- ISSN :
- 12709638
- Volume :
- 67
- Database :
- OpenAIRE
- Journal :
- Aerospace Science and Technology
- Accession number :
- edsair.doi...........0c621b76d8b6823669e21513bdc52347