TAS and wind estimation from radar data
TAS and wind estimation from radar data
复制标题
根据雷达数据进行 TAS 和风估计
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
S. Puechmorel
中科院分区：
文献类型：
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作者：
D. Delahaye;S. Puechmorel
准确的风速和风向估计是飞机航迹预测的关键。例如，基于这些数据，人们可以计算出一个扇区的进出时间，或者检测飞机之间的潜在冲突。由于这类应用需要实时计算和更新飞行路径，因此风向信息也必须实时可用。目前通过气象服务广播获得的风资料在地点和时间上的测量率都很小。本文提出了一种基于雷达航迹测量的风估计新方法。当机载真风速测量可用时，开发了一个线性模型，并使用卡尔曼滤波来产生高质量的风估计。当只有飞机位置测量可用时，可观测性分析表明，只有当轨迹有一个或两个转弯时，根据位于给定区域的飞机数量，才能估计风。基于这种可观测性条件，已经开发了一个和两个飞机情况下的风的封闭形式。通过这种方式，每架飞机在转弯时都可以被视为风传感器。在实际框架中进行评估后，我们的方法能够准确地估计风矢量。在这些局部风估计的基础上，利用向量样条插值得到全局空时风场估计，从而得到感兴趣区域的风图。风场计算的主要模式为浅水模式，该模式假定地转风。该风图的准确性取决于给定区域内估计的风的数量。通过与气象测量相关联，可以进一步改进估算。
Accurate wind magnitude and direction estimation is essential for aircraft trajectory prediction. For instance, based on these data, one may compute entry and exit times from a sector or detect potential conflict between aircraft. Since the flight path has to be computed and updated on real time for such applications, wind information has to be available in real time too. The wind data which are currently available through meteorological service broadcast suffer from small measurement rate with respect to location and time. In this paper, a new wind estimation method based on radar track measures is proposed. When on board true air speed measures are available, a linear model is developed for which a Kalman filter is used to produce high quality wind estimate. When only aircraft position measures are available, an observability analysis shows that wind may be estimated only if trajectories have one or two turns depending of the number of aircraft located in a given area. Based on this observability conditions, closed forms of the wind has been developed for the one and two aircraft cases. By this mean, each aircraft can be seen as a wind sensor when it is turning. After performing evaluations in realistic frameworks, our approach is able to estimate the wind vectors accurately. Based on those local wind estimates, a global space-time wind field estimation using vector splines is interpolated in order to produce wind maps in the area of interest. The underline model for wind field computation is Shallow-Water, which assumes geostrophic wind. The accuracy of this wind map is dependent of the number wind estimates in a given zone. Further improvements to the estimation can be made by correlating with meteorological measurements.