A Heuristic Methodology for Optimal Deployment of Radar Systems in a Constrained Area of Operation

Abstract

In emerging network-centric warfare scenarios, the location of sensors in the sensor-grid plays a dominant role in determining the effectiveness of air defence against enemy air threats. Maximising the coverage area of sensors in the sensor-grid, considering operational performance parameters, terrain features and deployability is a challenging task for military operational planners and commanders. Such optimisation problems may not be amenable to classical operations research techniques, or may require enormous computational time to arrive at the results as the decision space grows non-linearly for large areas of operation. In this paper, a novel methodology that uses a heuristic technique (genetic algorithms) to compute the optimal or near-optimal deployment locations for a given set of sensors in a constrained area of operation is proposed. The proposed methodology is illustrated with a number of case studies and a decision support tool is developed as an aid to the military commanders.

Modelling of the Military Helicopter Operation Process in Terms of Readiness

“…Due to the fact that the process under investigation has an established organisation (exploitation strategy), not all theoretically possible interstate transitions are allowed 22,25 . Test sample of helicopters has narrowed down the number of 72 theoretically possible passages to 30 allowed passages (Fig.…”

“…A separate area of application of Markov processes is the modelling of technical objects exploitation processes [21][22][23][24][25] , as well as their implementation in the analysis and evaluation of both availability 5,[26][27][28] and readiness [29][30][31][32][33] .…”

“…In studies on modelling exploitation processes, the reliability of the vehicle fleet defined as a function of the damage stream 21,29 , assessment of the degree and level of usability 30 , readiness 22,25,32 of an object or system of exploitation 27,28 , or population renewal including replacement according to age 23,34 often become the subject of tests.…”

“…The essence of mathematical modelling is to describe the examined phenomenon (process, system) using mathematical language. The modelling uses variables representing certain (and at the same time significant) from the point of view of the purpose properties of the examined phenomenon 22,24,38,43 . Examination of the exploitation system requires the identification of all important factors that define it.…”

The Opposition-Based Learning Parameter Adjusting Harmony Search Algorithm Research on Radars Optimal Deployment

“…With the rapid change of the battle eld environment, more and more radars and other equipment are used to detect targets through networking [1,2]. Under the threats and challenges of enemy invasion defense, the optimal deployment can make limited radar resources reasonably allocated to form a tight and reliable radar surveillance network and achieve the best combat e ectiveness [3,4]. More and more algorithms are applied into the radar optimal deployment.…”