scholarly journals Analysis of Non Linear Frequency Modulation (NLFM) Waveforms for Pulse Compression Radar

2018 ◽  
Vol 18 (1) ◽  
pp. 27 ◽  
Author(s):  
Muhamad Ridwan Widyantara ◽  
Sugihartono ◽  
Fiky Y. Suratman ◽  
Slamet Widodo ◽  
Pamungkas Daud
Keyword(s):  
Frequency Modulation ◽  
Doppler Effect ◽  
Pulse Compression ◽  
Weighting Function ◽  
Additive White Gaussian Noise ◽  
Linear Frequency Modulation ◽  
Sidelobe Level ◽  
Linear Frequency ◽  
Non Linear ◽  
Peak Sidelobe Level

Non Linear Frequency Modulation (NLFM) method can suppress the peak sidelobe level without additional windowing function. NLFM doesn’t require any weighting function because it has inbuilt one. NLFM has a variable frequency deviation function due to the relation between frequency and time of the signal which is not linear so that it is possible to suppress of peak sidelobe level. This paper studies the characteristic of various NLFM waveform, such as NLFM Tri Stage Piece Wise (TSPW), NLFM S, and NLFM Taylor. The study of Pulse Compression of NLFM waveform consists of three aspects. First, analysis of pulse compression performance. Second, analysis of background noise. Last, analysis of Doppler effects. The simulation is done using Matlab software. The lowest  value Peak Sidelobe Level (PSL)of NLFM TSPW is about -20 dB while NLFM S and NLFM Taylor are about -32 dB and -39 dB. Additive White Gaussian Noise (AWGN) and Doppler Effect influenced the value of PSL for each NLFM waveform. NLFM Taylor has the best NLFM waveform when the Doppler Effect and AWGN cause the value of PSL become high. Comparison between NLFM Taylor and Linear Frequency Modulation(LFM) is done in radar surveillance applications to analyze the detectability performance where the condition of Radar Cross Section (RCS) for each target has different significant value. The three targets are commercial airplanes, helicopter and fighter. For detectability performance, NLFM Taylor can detect more clearly than LFM conventional.

scholarly journals Modified PWNLFM Signal for Side-Lobe Reduction

2018 ◽  
Vol 7 (4.20) ◽  
pp. 4
Author(s):  
N. Adithya valli ◽  
Dr. D. Elizabath Rani
Keyword(s):  
Linear Function ◽  
Frequency Modulation ◽  
Pulse Compression ◽  
Weighting Function ◽  
Side Lobe ◽  
Linear Frequency Modulation ◽  
Side Lobe Level ◽  
Chirp Signal ◽  
Linear Frequency ◽  
Non Linear

Many applications in radar systems require low range side-lobe performance which is achieved by pulse compression processing. Most used chirp signal for this processing is linear frequency modulation (LFM) signal but with a presence of first high side-lobe level. Suppression of this side-lobe requires weighting function causing the reduction in signal to noise ratio at the receiver owing to mismatch loss. Non-linear chirp signals are introduced as a solution and became most practiced signals aimed at reducing side-lobes. In this paper, an overall piece wise non-linear frequency modulation chirp signal is designed by merging two stages, one with linear function and the other with a tangent based non-linear function. Simulation results show significant reduction in the sidelobe level of autocorrelation function when NLFM is generated in this method. 

scholarly journals Convolutional Windows for Side Lobe Reduction

2019 ◽  
Vol 8 (10) ◽  
pp. 3526-3529
Keyword(s):  
Frequency Modulation ◽  
Pulse Compression ◽  
Side Lobe ◽  
Linear Frequency Modulation ◽  
Side Lobe Level ◽  
Chirp Signal ◽  
Sidelobe Level ◽  
Linear Frequency ◽  
Radar Systems ◽  
Window Functions

A lot of applications in radar systems necessitate low range side-lobe performance which is achieved by pulse compression processing. Linear Frequency Modulation (LFM) signal is mainly used chirp signal for this processing. The paramount drawback in LFM is the first side-lobe level of -13dB at the receiver side. In this paper, LFM signal is modified by using simple two-stage piece wise linear frequency modulation (PWLFM) functions. The autocorrelation function of this PWLFM signal exhibited low peak sidelobe level ratio (PSLR) value compared to its counterpart LFM signal. An attempt is made to further reduce the side lobe values by using novel Convolutional windows. The simulation results confirm a significant side lobe reduction by the LFM signal designed using PWLFM functions when a more flexible Power of Cosine window function is applied compared to all other window functions.

scholarly journals Encoded Hybrid PSK/FSK Waveform for LPI Radar

2020 ◽  
Vol 8 (6) ◽  
pp. 2753-2760
Keyword(s):  
Frequency Modulation ◽  
Pulse Compression ◽  
Average Power ◽  
Side Lobe ◽  
Linear Frequency Modulation ◽  
Coincidence Detection ◽  
Side Lobe Level ◽  
Linear Frequency ◽  
Non Linear ◽  
Radar Waveforms

Since the advantage of pulse compression radar, the pseudo random codes and poly time codes and non linear frequency modulation has been mostly widely used low probability intercept (LPI) radar waveforms. By changing frequencies time to time in frequency modulation known as non-linear frequency modulation (frequency hopping (FH)), peak to side lobe ratio (PSLR) can be achieved to make less severe the covering effect of nearby targets and to improve the useful dynamic range. Adding an appropriate binary encoded ternary phase shift signal (PSK) as form as Binary encoded Hybrid-PSK/FSK (BEH PSK/FSK), the peak side lobe ratios are obtained very low values (e.g., PSLR<-70dB), similar to the antenna side lobes. In advanced microwave power amplifier technology, now a day’s using low peak to average power modules requires them to be amalgamated at the radio frequency (RF) stage in that way to obtain the required emitted radiated power. The deterministic waveforms are represents Noise waveform radar technology is a valid alternative. The pseudorandom waveform-realization of a noise process, the higher its bandwidth-time (or BT) product, the lower the (numerical) peak side lobe ratio. With practical Bandwidth-time values, the achievable peak side lobe using pure random is not sufficient the generated pseudorandom waveforms undergoes optimized genetic algorithm Hamming Scan (HS) to achieve optimized pseudo random (OBC), in order to achieve the desired side lobe level. This manuscript proposes a general analysis of the two modes of radar waveforms, i.e., Ternary and Binary alphabetic waveforms of coincidence detection.

scholarly journals Optimization of two-stage NLFM signal using Heuristic approach

2020 ◽  
Vol 13 (44) ◽  
pp. 4465-4473
Author(s):  
Chandu Kavitha ◽  
Keyword(s):  
Optimization Algorithm ◽  
Frequency Modulation ◽  
Pulse Compression ◽  
Piecewise Linear ◽  
Side Lobe ◽  
Linear Frequency Modulation ◽  
Main Lobe ◽  
Design And Optimization ◽  
Linear Frequency ◽  
Scripting Language

Background/Objectives: The design of appropriate Non-Linear Frequency Modulation (NLFM) signals continues to be the focus of research in radar pulse compression theory for sidelobe reduction. This study focuses on a heuristic design and optimization algorithm to optimize the side lobe values of the NLFM signal designed using two-piece wise linear frequency modulation (LFM) functions. Methods: 1) Heuristic search identifies the optimum B1, T1, and B2, T2, which yield the lowest sidelobe value of the designed function.2) Compute all the side lobe values of the designed NLFM signal using an algorithm developed in Python scripting language. To plot a complete contour map for all the calculated side lobe values, which helps identify the associated variations in the range of side lobe values. Finally, optimize the side lobe values keeping the main lobe width and time-bandwidth (BT) product unchanged by designing a dynamic optimization algorithm. Findings: The algorithm developed considered all side lobe levels after the main lobe for optimization. The focus is mainly on the peak sidelobe ratio (PSLR) value without affecting the other parameters. The results demonstrate that the achieved side lobes exhibit their desired levels. Novelty: The method is useful in all types of hardware associated with weather radar applications to military solutions. The technique can be extended to other multistage signals consisting of piecewise linear Segments. Keywords: Contour; LFM; NLFM; optimization; PSLR

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