International Journal of Application or Innovation in Engineering & Management (IJAIEM) Web Site: www.ijaiem.org Email: editor@ijaiem.org Volume 3, Issue 11, November 2014 ISSN 2319 - 4847 Volume 3, Issue 11, November 2014 Page 188 ABSTRACT Forward scattering radar (FSR) is a special case of bistatic radar that can be used for automatic ground target detection and classification, the interest in FSR is rises after its capability in target classification is validated. The recent development of the FSR system for ground target classifications did not consider a rough environment analysis. This paper introduces and analyze and study to the automatic ground target classification using Neural network under different noisy conditions this include the overall classification system and the extraction of features from the radar measurements provided results have shown the effectiveness of neural network as potential classifier for ground targets even in sever noisy environment Keywords: Forward Scattering Radar, Neural network, Signal to noise ratio 1.INTRODUCTION Forward scattering radar (FSR) is a special configuration of bistatic radar that occurs when the angle is 180 degree in Bistatic radar. Currently there has been increase of interest of researches in this area .This is due to FSR has many features include relatively simple hardware; an enhanced target radar cross-section (RCS) [1-4] .The Principles and basics of FSR can be found in the works of Willis [1]. The forward scattering RCS mainly depends on the target’s physical cross section and the wavelength, and is independent of the target’s surface shape. Most of the recent studies and results of FSR reported in the stated literatures have only been carried out in a small number of scenarios specialty for the ground targets. Recent study focusing on ground target classification [3][5] did not consider the operating rough environment which may include high noise contributing to the received signal .this contributing noise may significantly affects the classification process 2.FORWARD SCATTERING RADAR BASICS AND THEORY Bistatic radars have been used extensively in World War I and II for airborne targets [1]. However, their geometry was similar to the forward scatter configuration, where targets fly near the transmitter-receiver baseline. Since the coverage area is very narrow, only targets that penetrated a single given fence could be detected. Therefore they found to be of very limited use for air target detection.[2]. Consequently, most of the early forward scatter fences were eventually replaced by monostatic radars which have better spatial coverage area and location accuracy [3][5] the theory behind FSR is rather more complicated and far from full development. This section summarizes the basic technical of FSR in terms of signal scattered. More detail about this subject can be found in [1-10] The basic FSR system is shown in Fig.(1) which comprises of transmitter, Tx with fc central frequency with an appropriate wavelength, λ and a receiver, Rx separated by a distance, b from the transmitter. The target, Ta is assumed to be moving along a trajectory that crosses the baseline with speed, V has zero elevation and the system operates in a ground plane. For a moving target, the shadow signal experiences Doppler shift, dbr f and can be evaluated as: [6] β Transmitter Receiver b V Target Figure 1: FSR general layout Target Classification in Forward Scattering Radar in Noisy Environment Mohamed Khala Alla H.M, Mohamed Kanona and Ashraf Gasim Elsid School of telecommunication and space technology, Future university Africa road ,Khartoum, Sudan