Research On Key Algorithms For Airborne Weather Radar Simulation Data Incentive System Of AESS

Airborne weather radar is an important part of Aircraft EnvironmentSurveillance System (AESS), it is essential for safe flight. But the directresearch of it costs too much, and the research cycle takes long time. Realsimulation of radar system can reduce research and development costs.Researchers can not only test the stability and the limitations of signalprocessing technology, but also can check any ignored factors in designprocess. This article aimed at the simulation system for airborne weatherradar of AESS, according to the satellite imagery in front of the aircraft,dynamic inverting the wind field and cloud field of interested region, andall the obtained data as an external incentive, will be send to the simulationsystem of airborne weather radar.This article focused on the key algorithms of data incentive for thesimulation system of airborne weather radar: wind field inversion, cloudmicrophysical modeling, dynamic simulation of cloud field.For wind field inversion, adoption the finite difference method,projection method, and low dimensional fluid motion estimator. Usingfinite difference method and projection method, can fast solve the N-Sequations, recur the wind field of two consecutive images at any pointedtime. The low dimensional fluid motion estimator introduces thelow-dimensional parametric representation into dealing with consecutiveimages. Compared with traditional optical flow, it is much higher inprecision. The obtained wind field can be the initial value of N-S equation.In combining the two methods, we can get a more accurate wind field.This is an innovation point.During the cloud densities updating process, employing Stam’s method, greatly simplified the computation. Using the cellular automatontechnology, through simple Boolean operations can simulate the movementof cloud particles, can effectively simulate the formation and disappearingof cloud. In the dynamic inversion of cloud field procedure, added theactual physical model to the cloud formation, which is simplified. Thedynamic three-dimensional cloud field obtained, not only looks realistic,but also has the authenticity of physical model. This is another innovationpoint.Software simulation results show that the results are in line with theactual weather information that the satellite pictures shown, generally meetthe requirements of AESS digital prototyping.