Adaptive resource management algorithm for target tracking in radar network based on low probability of intercept

Shi, Chenguang; Zhou, Jianjiang; Wang, Fei

doi:10.1007/s11045-017-0494-8

Cited by 15 publications

(18 citation statements)

References 36 publications

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“…It should be pointed out that the predefined target detection constraint β SINR is set to be −2.5 dB, which is approximately equivalent to the values of β MI = 0.466 nats for a desired target parameter estimation performance (Romero et al, ; Shi et al, ). In order to solve the problems of LPI‐based jamming waveform design Problem 1 and Problem 2 , it is also assumed that the precise knowledge of the target spectra, the PSDs of the signal‐dependent clutters, and the radar‐transmitted waveforms are perfectly estimated by the smart jammer (Shi, Zhou, & Wang, ; L. L. Wang et al, ).…”

Section: Performance Evaluation Results and Discussionmentioning

confidence: 99%

“…Besides, the total transmitted jamming power of the uniform jamming waveform in both criteria is also presented in Figure , where the uniform jamming waveform design methods are considered as the corresponding benchmarks. As introduced in Shi, Zhou, and Wang () and L. L. Wang et al (), the uniform jamming waveform spreads the barrage noise jamming power averagely in the whole frequency band without any prior information about the target, clutter, and radar‐transmitted waveforms. As predicted in previous sections, for the same SINR/MI threshold value, the LPI performance improvement is quite apparent compared with the uniform jamming waveform design schemes which are usually adopted in traditional barrage noise jamming because of not employing the prior knowledge.…”

Section: Performance Evaluation Results and Discussionmentioning

confidence: 99%

“…Nowadays, the concept of low probability of intercept (LPI) should be taken into account in designing radar systems (Pace, ; Schleher, ; Shi et al, ; Shi, Zhou, & Wang, ; Zhang et al, ). Precisely, large revisit interval, low transmission power, short dwell time, ultralow sidelobe antenna, and waveform optimization can result in better LPI performance of radar system.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Jamming Waveform Design for Distributed Multiple‐Radar Architectures Based on Low Probability of Intercept

et al. 2019

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This paper investigates the problem of low probability of intercept (LPI)‐based adaptive jamming waveform design for distributed multiple‐radar architectures. Such a smart jammer system adopts a multibeam working mode, where multiple simultaneous jamming beams are synthesized to interfere with multiple radars independently. The primary objective of the smart jammer is to minimize the total jamming power by optimizing the transmitted jamming waveform while the achieved signal‐to‐interference‐plus‐noise ratio (SINR) and mutual information (MI) between the received echoes from the target at each radar receiver and the target impulse responses are enforced to be below specified thresholds. First, the expressions of SINR and MI are derived to characterize target detection and characterization performance, respectively. Then, two different LPI‐based jamming waveform design strategies are proposed to minimize the total noise jamming power by optimizing the jamming waveform while the achieved SINR/MI is enforced to be below a certain threshold. The resulting optimization problems are solved analytically by employing the technique of Lagrange multipliers. With the aid of some numerical examples, it is illustrated that the two schemes result in different jamming waveform design results, which is useful to guide jamming power allocation for various jamming tasks. It is also shown that the LPI performance of the smart jammer can be efficiently improved by exploiting the proposed jamming waveform design criteria.

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Section: Performance Evaluation Results and Discussionmentioning

confidence: 99%

Section: Performance Evaluation Results and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive Jamming Waveform Design for Distributed Multiple‐Radar Architectures Based on Low Probability of Intercept

et al. 2019

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“…Then, the mean period of simultaneous overlaps of two window junctions is expressed as

T_{M} = \frac{\frac{T_{I}}{τ_{I}} \frac{normalΔ T}{T_{normald, i}}}{\frac{1}{τ_{I}} + \frac{1}{T_{normald, i}}},

where Δ T is the revisit interval. Hence, the spatial‐time‐frequency intercept probability that an intercept occurs during the time T d, i can be obtained as follows (Shi et al, ; Yan et al, ):

p_{stf} = 1 - K_{0} \exp ((), - \frac{T_{normald, i}}{T_{M}}),

where

K_{0} = 1 - \frac{T_{I}}{τ_{I}} \frac{normalΔ T}{T_{normald, i}} = 1

since τ I ≪ T I and T d, i ≪Δ T .…”

Section: Jtsrm Strategymentioning

confidence: 99%

“…where ΔT is the revisit interval. Hence, the spatial-time-frequency intercept probability that an intercept occurs during the time T d,i can be obtained as follows (Shi et al, 2017;Yan et al, 2016):…”

Section: 1029/2018rs006584mentioning

confidence: 99%

Joint Transmitter Selection and Resource Management Strategy Based on Low Probability of Intercept Optimization for Distributed Radar Networks

et al. 2018

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In this paper, a joint transmitter selection and resource management (JTSRM) strategy based on low probability of intercept (LPI) is proposed for target tracking in distributed radar network system. The basis of the JTSRM strategy is to utilize the optimization technique to control transmitting resources of radar networks in order to improve the LPI performance while guaranteeing a specified target‐tracking accuracy. The weighted intercept probability and transmit power of radar networks is defined and subsequently employed as the optimization criterion for the JTSRM strategy. The resulting optimization problem is to minimize the LPI performance criterion of radar networks by optimizing the revisit interval, dwell time, transmitter selection, and transmit power subject to a desired target‐tracking performance and some resource constraints. An efficient and fast three‐step solution technique is also developed to solve this problem. The presented mechanism implements the optimal working parameters based on the feedback information in the tracking recursion cycle in order to improve the LPI performance for radar networks. Numerical simulations are provided to verify the superior performance of the proposed JTSRM strategy.

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A Novel Pythagorean Hesitant Fuzzy WASPAS Method for Evaluating the RF Stealth Performance of Aviation Swarm in Penetration Scenario

Yang¹,

Wang²,

Zhu³

et al. 2021

Lecture Notes in Electrical Engineering

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Adaptive resource management algorithm for target tracking in radar network based on low probability of intercept

Cited by 15 publications

References 36 publications

Adaptive Jamming Waveform Design for Distributed Multiple‐Radar Architectures Based on Low Probability of Intercept

Adaptive Jamming Waveform Design for Distributed Multiple‐Radar Architectures Based on Low Probability of Intercept

Joint Transmitter Selection and Resource Management Strategy Based on Low Probability of Intercept Optimization for Distributed Radar Networks

A Novel Pythagorean Hesitant Fuzzy WASPAS Method for Evaluating the RF Stealth Performance of Aviation Swarm in Penetration Scenario

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