Electrical Engineering

Abstract: This paper presents a compact, recursive, non-linear, filter, derived from the Gauss-Newton (GNF), which is an algorithm that is based on weighted least squares and the Newton method of local linearisation. The recursive form (RGNF), which is then adapted to the Levenberg-Maquardt method is applicable to linear/nonlinear of process state models, coupled with the linear/nonlinear observation schemes.

Abstract Inverse synthetic aperture radar (ISAR) imaging of sea vessels is a challenging task because their 3-D rotational motion over the coherent processing interval (CPI) often leads to blurred images. The selection of the duration of the CPI, also known as the coherent processing time window length (CPTWL), is critical because it should be short enough to limit the blurring caused by the 3-D rotational motion and long enough to ensure that the desired cross-range resolution is obtained.

Abstract—As mobile devices become both computing tools as well as communications devices, mobile cloud computing provides a means to enhance the computational capabilities of these devices. As an initial step in the development of this technology, this paper proposes a framework that identifies and defines various important aspects of mobile cloud computing.

1 Abstract Significant developments have been made in space-based radar systems and technology since the first satellite with a radar payload was launched (the Gemini radar). This paper presents an overview of some of the remote sensing applications of satellite imaging radars, which range from topographic mapping to forest and climate monitoring to the detection of oil spills and the monitoring of natural disasters, to name just a few.

ABSTRACT: This paper discusses the current status of imaging radar systems deployed on spacecraft and airborne platforms, such as aircraft and unmanned airborne vehicles (UAVs). Imaging radar technology has advanced considerably over the last twenty years, and the user can now be fairly certain of finding a sensor ideal for a specific application. The objective of the paper is to demonstrate some of the available systems and current applications, and to indicate what will be available in the near future.

Abstract Inverse synthetic aperture radar (ISAR) is an imaging technique that is dependent on an object's rotational motion over a coherent processing interval. Maritime vessels and aircraft possess 3-D rotational motion, whereas it is only their ISAR contributing motion that is useful to the ISAR imaging process; the contributing motion consists of the Doppler generating axis and the effective angle of rotation.

Abstract The classification of ship targets using low resolution down-range radar profiles together with preprocessing and neural networks is investigated. An implementation of the Fourier-modified discrete Mellin transform is used as a means for extracting features which are insensitive to the aspect angle of the radar. Kohonen's self-organizing map with learning vector quantization (LVQ) is used for the classification of these feature vectors. The use of a feedforward network trained with the backpropagation algorithm is also investigated.

Abstract In the design and implementation of synthetic-aperture radar (SAR) processors, it is useful to have a test data base with which to test processing algorithms and investigate parameters such as the point spread function. Simulated SAR data provides such a controlled data base. This paper reports on the generation of airborne and satellite SAR data using a combination of home-grown C software and a commercial radar simulation package.