Abstract
This paper presents a novel low probability of intercept (LPI) optimization framework in radar network by minimizing the Schleher intercept factor based on minimum mean-square error (MMSE) estimation. MMSE of the estimate of the target scatterer matrix is presented as a metric for the ability to estimate the target scattering characteristic. The LPI optimization problem, which is developed on the basis of a predetermined MMSE threshold, has two variables, including transmitted power and target assignment index. We separated power allocation from target assignment through two sub-problems. First, the optimum power allocation is obtained for each target assignment scheme. Second, target assignment schemes are selected based on the results of power allocation. The main problem of this paper can be considered in the point of views based on two cases, including single radar assigned to each target and two radars assigned to each target. According to simulation results, the proposed algorithm can effectively reduce the total Schleher intercept factor of a radar network, which can make a great contribution to improve the LPI performance of a radar network.
Highlights
Radar emitters are threatened by many passive threats, such as electronic intelligence (ELINT) systems, electronic support measures (ESM), anti-radiation missiles (ARM), and radar warning receivers (RWR) [1]
We investigate a novel low probability of intercept (LPI) optimization framework in a radar network system for multiple targets tracking based on two cases, including single radar assigned to each target and two radars assigned to each target
For a predetermined threshold of MMSEq, the aim of this paper is to adaptively allocate the transmitted power of radars, which can result in minimizing the total Schleher intercept factor of the radar network, subject to the limit of MMSEq based on the criterion given in Equation (20)
Summary
Radar emitters are threatened by many passive threats, such as electronic intelligence (ELINT) systems, electronic support measures (ESM), anti-radiation missiles (ARM), and radar warning receivers (RWR) [1]. All these threat systems perform three basic functions: detection, classification, and recognition. With many advanced methods implemented in threat systems, such as the specific emitter identification (SEI) method, the probability of correct classification and recognition in ESM/ELINT systems has increased significantly [2,3,4] For these reasons, the low probability of intercept (LPI) problem of radar emitters is becoming an indispensable and vital problem in the contemporary battlefield [5,6,7]. Multiple-input multiple-output (MIMO) radar systems [8,9]
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