Determination of land surface temperature using precipitable water based Split-Window and Artificial Neural Network in Turkey

Land surface temperature (LST) calculation utilizing satellite thermal images is very difficult due to the great temporal variance of atmospheric water vapor in the atmosphere which strongly affects the thermal radiance incoming to satellite sensors. In this study, Split-Window (SW) and Radial Basis Function (RBF) methods were utilized for prediction of LST using precipitable water for Turkey. Coll 94 Split-Window algorithm was modified using regional precipitable water values estimated from upper-air Radiosond observations for the years 1990–2007 and Local Split-Window (LSW) algorithms were generated for the study area. Using local algorithms and Advanced Very High Resolution Radiometer (AVHRR) data, monthly mean daily sum LST values were calculated. In RBF method latitude, longitude, altitude, surface emissivity, sun shine duration and precipitable water values were used as input variables of the structure. Correlation coefficients between estimated and measured LST values were obtained as 99.23% (for RBF) and 94.48% (for LSW) at 00:00 UTC and 92.77% (for RBF) and 89.98% (for LSW) at 12:00 UTC. These meaningful statistical results suggest that RBF and LSW methods could be used for LST calculation.     

Multipath Separation-Direction of Arrival (MS-DOA) with Genetic Search Algorithm for HF channels

Direction-of-Arrival (DOA) defines the estimation of arrival angles of an electromagnetic wave impinging on a set of sensors. For dispersive and time-varying HF channels, where the propagating wave also suffers from the multipath phenomena, estimation of DOA is a very challenging problem. Multipath Separation-Direction of Arrival (MS-DOA), that is developed to estimate both the arrival angles in elevation and azimuth and the incoming signals at the output of the reference antenna with very high accuracy, proves itself as a strong alternative in DOA estimation for HF channels. In MS-DOA, a linear system of equations is formed using the coefficients of the basis vector for the array output vector, the incoming signal vector and the array manifold. The angles of arrival in elevation and azimuth are obtained as the maximizers of the sum of the magnitude squares of the projection of the signal coefficients on the column space of the array manifold. In this study, alternative Genetic Search Algorithms (GA) for the maximizers of the projection sum are investigated using simulated and experimental ionospheric channel data. It is observed that GA combined with MS-DOA is a powerful alternative in online DOA estimation and can be further developed according to the channel characteristics of a specific HF link.     

Long term and safe relative orbit design for heterogeneous spacecraft clusters

The problem of obtaining long term relative orbit configurations for spacecraft clusters with realistic operational considerations such as safety, station keeping and inter-spacecraft distances is addressed. Two different approaches are developed for station keeping and safety objectives. In the first approach, relative orbit configurations, or relative TLEs, are found minimizing deviations from reference mean orbit which would maximize the station-keeping objective. In second one, relative configurations are found from a reference initial condition by minimizing probability of collision, hence maximizing the safety objective, between the spacecraft in the cluster which are propagated numerically through a high precision orbit propagator. For the design optimization, a derivative free algorithm is proposed. Effectiveness of the approaches is demonstrated through simulations. Using this design framework, several configurations can be found by exploring the limits of the clusters in terms of spacecraft number, distance bounds and probabilities of collision for long time intervals.