Multi-objective Heuristic Design Approach for SAR Mission for Monitoring Local Target Area

作者: Hae-Dong Kim , Jae-Dong Seong

DOI: 10.1007/S42405-018-0129-9

关键词: Ground trackHeuristic (computer science)Real-time computingComputer sciencePoint targetBistatic radarSynthetic aperture radarSatellite constellationSatelliteOrbit (dynamics)

摘要: The Korea first synthetic aperture radar (SAR) satellite with a 1-m resolution—Korea Multi-purpose Satellite-5 (KOMPSAT-5)—was successfully launched in 2013, and its successors will be continuously to monitor specific target areas. major requirements of the orbit design for KOMPSAT-5 are that mean average revisit time (ART) over Korean peninsula is no longer than 24 h repeat ground track guaranteed. For this type problem, an iterative tedious process may used derive appropriate mission satisfy requirements. During process, sophisticated coverage analysis software should employed evaluate ART local area. Moccia et al. (Acta Astronaut 47(11):819–829, 2000) presented feasibility study new space-based observation technique using bistatic SAR performed numerical simulation estimate measurement accuracy bright point position velocity. Kim Chang (Aerosp Sci Technol 40:17–32, 2015) developed optimal scheduling method employing genetic algorithm (GA) reduce system response constellation. Wei Chunsheng (Adv Sp Res 50:272–281, 2012) proposed distributed satellite-borne error-propagation model monostatic determine key parameters single satellite. Apart from mission, Earth-observation missions area or has been studied by others. Abdelkhlik (J Guid Control Dyn 29(5):1231–1235, 2006) utilized RGT concept natural orbits visiting without use propulsion systems. Spacecr Rocket 46(3):725–728, 2009) strategy GA search current temporary achieve reconnaissance particular site low-Earth-orbit during period. We propose effective approach Here, transmitted power bus system, respectively. To our knowledge, previous studies have considered kind problem. simultaneously consider power, multi-objective heuristic algorithms including GEs, particle swarm optimization, differential evolution used, their performances compared. computational authors based on optimization Matlab® powerful tool STK®. Therefore, adaptable various types designs having complex regarding both particularly monitoring

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