IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 04 Issue: 06 | June-2015, Available @ http://www.ijret.org 544 CYCLOSTATIONARY ANALYSIS OF POLYTIME CODED SIGNALS FOR LPI RADARS Metuku Shyamsunder 1 , Kakarla Subbarao 2 1 Assistant Professor,Department of ECE, Osmania University, Telangana, India 2 Professor, Department of ECE, CBIT, Telanagana, India Abstract In Radars, an electromagnetic waveform will be sent, and an echo of the same signal will be received by the receiver. From this received signal, by extracting various parameters such as round trip delay, doppler frequency it is possible to find distance, speed, altitude, etc. However, nowadays as the technology increases, intruders are intercepting transmitted signal as it reaches them, and they will be extracting the characteristics and trying to modify them. So there is a need to develop a system whose signal cannot be identified by no cooperative intercept receivers. That is why LPI radars came into existence. In this paper a brief discussion on LPI radar and its modulation (Polytime code (PT1)), detection (Cyclostationary (DFSM & FAM) techniques such as DFSM, FAM are presented and compared with respect to computational complexity. Keywords—LPI Radar, Polytime codes, Cyclostationary DFSM, and FAM --------------------------------------------------------------------***---------------------------------------------------------------------- 1. INTRODUCTION The radar is an abbreviation for RAdio Detection And Ranging expression. In general, the radar systems use modulated waveforms and directive antennas to transmit electromagnetic energy into a specific volume in space to search for targets. Objects (or targets) within a special search volume will reflect back to the radar a portion of this energy (radar returns or echoes). These echoes are processed by the radar receiver to extract target information such as range, velocity, angular position, and other target identifying characteristics [1].A low probability of intercept (LPI) radar is defined as radar that uses a special emitted waveform intended to prevent a non cooperative intercept receiver from intercepting and detecting its emission. The LPI radar has different modulation and detecting techniques of them we are going to discuss following. A study conducted on the implementation of Barker code and linear frequency modulation pulse compression technique has shown that the SNR and Range resolution were improved even for targets having very low RCS, but failed to prove quantitatively [2]. A group of scientists presented modeling and analysis of LPI radar signals using Barker and polyphase codes which only gives the time and frequency changes, but could not extract the required parameters such as center frequency, Bandwidth, and code rate [3]. FMCW modulated LPI signals were analyzed using Wiener Ville Distribution, the performance of which is limited for the estimation of the center frequency in the frequency agility conditions [4]. This paper focused on the Polytime codes modulated LPI signals and extraction of its parameters using efficient methods of cyclostationary signal processing. The analysis performed under different SNR conditions with different methods such as DFSM, FAM and compared quantitatively. 2. POLYTIME CODE (T1(n)) The Polytime codes are counterparts of polyphase codes in which phase along with time spent at each phase state will changes. There are four types of Polytime codes T1, T2, T3 and T4 out of which T1 is discussed below. The T1, T2 codes arise from stepped-RF waveform whereas the T3, T4 from linear-FM waveforms. T1(n) is an approximation to stepped-RF waveform with zero beat at its leading edge. The „n‟ indicates the number of phase states used to approximate the underlying waveform. The proposed work uses only two phase states (0 and 180). The signal is of 16μSec is divided into four segments each of 4μSec. Among the four segments the first segment has no signal, and the second segment has one full cycle (3600). The third segment consists of two full cycles (7200), and the fourth segment has three full cycles (10800) resulting in a total accumulated phase of 21600. The Fig.1 shows the unwrapped accumulated phase and quantized wrapped phase of a stepped-RF signal. The above wrapped phase quantized to 00 and 1800 can be directly generated by using the equation.(1) φt = MOD  2π n INTkt − jT jn T ,2π (1) n = number of phase states k = number of segments T = Total code duration j = segment number