A Study Of Real-time Task Scheduling Technology Based On Adaptive Data-rate Control In Phased Array Radar

A phased array radar(PAR)is capable of quick beam change within the order of magnitude of microsecond,making it an important leap in radar system.It breaks the limits of fixed scanning mode,fixed transmission power,and fixed dwell time,etc.,inherent in conventional mechanical scanning radars,and hence enhances radar performance and capability.In airborne application,it improves appreciably the mission implementation capability and reliability of combat aircraft avionics.Because of this,PAR has become the mainstream system for airborne fire control,monitoring,and reconnaissance radars.The system advantage can be put to the fullest use by intelligent management and utilization of a PAR system,which provides greater control freedom in dimensions like space,time,frequency,energy,and processing.In recent years,airborne PAR began to be used in model development in China,but China lags behind America and European military giants in radar resource management.Technology and methodology research effort in PAR system resource management is therefore of great theoretical importance and engineering and practical significance to bolstering and exploiting the operation efficiency offered by a PAR system.Mission data control technology and mission scheduling & decision-making technology are two important research fields in airborne PAR resource management technology.At the present time,tracing data rate can be determined using quite a few available algorithms,most of which however have not considered sampling interval,tracing algorithms,mission scheduling,or other factors,or the relationship among them;in addition,there has been insufficient simulation demonstration of how to select a proper tracking sampling interval for the purpose of real-time mission scheduling.Based on target track tracing filtering covariance theory,the work presented in this paper carried out research on self-adapting data rate control,real-time task scheduling,etc.,developed an appropriate solution,and demonstrated the efficacy of this solution by simulation.The principal work is described below:1.Studying on target track tracing filtering covariance theory and,on the basis of classical Kalman filtering,describing the method by which the extended Kalman filtering and the interactive multi-model are used to compute the track tracing filtering covariance.2.Studying on self-adapting data rate control problem.Four computation methods of expected revisit time are developed,i.e.,formula,recurrence,predicted covariance threshold,and predefined covariance threshold,of which the formula and the predefined covariance threshold methods were compared by simulation,with the results suggesting that the formula method is better suited to computing tracing data rate in airborne applications.From this,a track filtering covariance based self-adapting data rate control technology is proposed.3.Studying on real-time mission scheduling.After reviewing traditional scheduling methods,two mission scheduling methods suitable for engineering implementation are advanced: Radar comprehensive mission planning based scheduling and comprehensive priority based self-adapting optimization scheduling.Both methods were simulated in airborne simulation scenarios that incorporated the motion characteristics of different targets.Simulation results suggest that both methods improved the utilization efficiency of radar resources and,in particular,the comprehensive priority based self-adapting optimization scheduling demonstrated good target maneuverability follow-up with respect to allocation of time resource,therefore using and allocating radar resources more properly.This paper focuses on the management of resources of individual PARs,further research being needed on the management of networked multi-sensors radar resources.