Particle Swarm Algorithm-based Navigation Waveform Design And Optimization

Global Navigation Satellites System (GNSS) can provide high-precision positioning,speed measurement and timing services,it can bring enormous social and economicbenefits. Therefore, global navigation satellite system has now become one of the criticalinfrastructure of modern society.The navigation signal structure design is the core of the the navigation satellitessystem, which determines navigation satellites system’s congenital performance."Signal waveform design" is a key link in the "Navigation signal structure design", chipsignal waveform determines the main features of the navigation signal’s autocorrelationfunction and power spectrum, thus affecting the system’s key performance indicatorssuch as positioning accuracy, anti-multipath compatibility, anti-jamming compatibility,compatibility and interoperability, so design excellent navigation signal waveform is veryessential.This paper studies the current situation of domestic and international navigationsignal design, detailedly analyze the various signal waveforms of the mainstreamnavigation satellites system, and based on this analysis integrated drawn navigation signalwaveform design trends; then this paper proposes a " local particle swarmalgorithm-based navigation waveform optimization algorithm". It’s basic idea is: base onthe mathematical modeling of the signal waveform and seting the evaluation criteria,using local particle swarm algorithm to optimize the waveform;then I improve“localparticle swarm algorithm” by combining with “quasi-Newton method”, we call it"combined algorithm", this algorithm can quickly find the best waveform under setconditions, and through simulationthis I proved this algorithm has both “globaloptimization ability” and “faster convergence ability”; finally,I use the penalty functionmethod in the optimization algorithm and get a signal waveform of lower power outsidethe band.