Fuzzy logic approach for prioritisation of radar tasks and sectors of surveillance in multifunction radar

Miranda, Sergio L.; Baker, Chris; Woodbridge, K.; Griffiths, Hugh

doi:10.1049/iet-rsn:20050106

Cited by 62 publications

(50 citation statements)

References 4 publications

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“…All the functions or the tasks are coordinated by a central component RRM in the radar system. This RRM component is critical to the success of a MFR since it maximizes the radar resource usage in order to achieve optimal performance [6,8,9].…”

Section: Introductionmentioning

confidence: 99%

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A Comparative Study on different AI Techniques towards Performance Evaluation in RRM(Radar Resource Management)

Madhusudhan¹,

Nazim²

2012

IJARAI

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Abstract-The multifunction radar (MFR) has to make a decision as to which functions are to be performed first or which must be degraded or even not done at all when there are not enough resources to be allocated. The process of making these decisions and determining their allocation as a function of time is known as Radar Resource Management (RRM). The RRM has two basic issues: task prioritization and task scheduling. The task prioritization is an important factor in the task scheduler. The other factor is the required scheduling time, which is decided by the environment, the target scenario and the performance requirements of radar functions. The required scheduling time could be improved by using advanced algorithm [1, 6].

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Section: Introductionmentioning

confidence: 99%

“…It is also very important that the information in respect of radar resource management is presented to the radar operator at all times [8,9].…”

Section: A Introduction To Ai Techniquesmentioning

confidence: 99%

A Comparative Study on different AI Techniques towards Performance Evaluation in RRM(Radar Resource Management)

Madhusudhan¹,

Nazim²

2012

IJARAI

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“…Stoffel [4] 은 고정형 우선 순 위와 인공 신경망을 이용한 휴리스틱 탐색 기법을 비교하여 후자가 탐색과 추적 성능의 향상을 가져온 다고 보고하였다. 이외의 적응형 우선 순위 선정 방 식으로는 인공 신경망을 사용한 기법 [5] , 퍼지 추론 시스템(Fuzzy Inference System: FIS)을 이용한 기법 들이 있다 [6], [7] . 이러한 기존 적응형 기법 중에서 실 제 시스템에 적용된 예는 Barbaresco의 FIS [6] 가 있다.…”

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A Study of Fuzzy Inference System Based Task Prioritizations for the Improvement of Tracking Performance in Multi-Function Radar

Kim

Park²,

Kim³

et al. 2013

The Journal of Korean Institute of Electromagnetic Engineering

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This paper presents the improvement of tracking performance using fuzzy inference system based task prioritizations for multi-function radars. The presented technique calculates elemental priorities using track information of a target and obtain the total priority from fuzzy inference system of each fuzzy set's membership function. In this paper, we proposed the task prioritization algorithms based on fuzzy inference system, and evaluated the tracking performance on multi-function radar scenario using it. As a result, we confirmed that excellent performance could be achieved when using the proposed algorithm.

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“…, [6] , 은닉 마르 코프 모델(HMM)이나 마르코프 결정 모델(MDP) 구 조 하에서 동적 프로그래밍을 통해 문제를 해결하는 방법 [7] , QoS(Quality of Service)를 목적 함수로 두는 Q-RAM 알고리즘 [8], [10] [12] .…”

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Beam Scheduling Algorithm of Multi-Function AESA Radar Based on Dispatching Rules

Roh¹,

Ahn²,

Kim³

2012

The Journal of Korean Institute of Electromagnetic Engineering

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AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability, compared with mechanically scanned array radar. AESA radar brings a new challenges, radar resource management(RRM), which is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed the several dispatching rules for radar beam scheduling, and compared the performance on the multi-function radar scenario. We also showed that the dispatching rule which differently applying SPF(Shortest Processing time First) and ERF(Earliest Request time First) according to beam processing latency is the most efficient.

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Fuzzy logic approach for prioritisation of radar tasks and sectors of surveillance in multifunction radar

Cited by 62 publications

References 4 publications

A Comparative Study on different AI Techniques towards Performance Evaluation in RRM(Radar Resource Management)

A Comparative Study on different AI Techniques towards Performance Evaluation in RRM(Radar Resource Management)

A Study of Fuzzy Inference System Based Task Prioritizations for the Improvement of Tracking Performance in Multi-Function Radar

Beam Scheduling Algorithm of Multi-Function AESA Radar Based on Dispatching Rules

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