Proceedings of the 11 th ICEENG Conference, 3-5 April, 2018 16-GNC Military Technical College Kobry El-Kobbah, Cairo, Egypt 11 th International Conference on Electrical Engineering ICEENG 2018 A New Sidelobe Cancellation Method for LFM Radars By Abstract—Pulse Compression technique is a vital tool commonly used in radar to increase range resolution and signal to noise ratio. Pulse compression allows achieving the performance of a shorter pulse using a longer pulse and hence gain of a large spectral bandwidth. Unwanted signals from sidelobes returns affect the detection capability of any radar. Different sidelobe reduction/cancellation techniques based on pulse compression for Linear Frequency Modulated (LFM) radars have been deployed and addressed before. In this paper, a new optimum filter for enhancing radar detection capabilities of LFM radars is introduced. The proposed filter response is compared with the windowed classical matched filter response associated with Hamming window function. The filter is implemented using Software Defined Radio (SDR). A practical test has been carried to investigate its performance. Results show superior performance of our proposed matched filter compared to that of classical versions Index Terms— Pulse compression, LFM, Optimum filter, Range resolution, Sidelobe cancellation, SDR. INTRODUCTION Pulse Compression (PC) techniques are used to obtain range resolution advantage of short pulses while maintaining long range detection ability of wider transmitted pulses. It is usually implemented through modulating the transmitted waveform in either phase or frequency providing a method to further resolve targets which may have overlapping returns [1]. The costs of applying pulse compression include added transmitter and receiver complexity, and must contend with time sidelobes masking weak useful signal appearance. Sidelobe reduction/cancellation techniques have been widely used to overcome this problem and consequently enhance response of the identified or matched filter [1,2]. For LFM signal, range resolution is given by: Ahmed Azouz, Sameh Ghanem, and Abdelrahman Elbardawiny