Dayat Kurniawan

Sidelobe suppression on pulse compression using curve-shaped nonlinear frequency modulation

Pulse compression is a method for improving the range resolution of the radar systems. Linear Frequency Modulation (LFM) is a type of pulse compression which is commonly used in the radar applications because of its simplicity and Doppler tolerance. However this method provides relatively high first peak sidelobe level within around -13.3 dB. This paper presents a developed curve-shaped Nonlinear Frequency Modulation (NLFM) using second degree polynomial approach for radar pulse compression in order to reduce the sidelobe level. The radar signal is assumed has bandwidth 30 MHz while the length of pulse signal as long as 10e-6 s. The curve-shaped chirp waveform is formed by the polynomial equation utilizing the LFM waveform as the base line. According to the simulation results and analysis, using a certain polynomial equation, the curve-shaped NLFM with negative orientation provides lower sidelobe level than the LFM. The best first peak sidelobe level achieved by this proposed NLFM is approximately -18.6 dB.

Switching CA/OS CFAR using neural network for radar target detection in non-homogeneous environment

This paper presents the switching CA/OS CFAR using neural network for improving the radar target detection in non-homogeneous environment. This method uses one of between CA-CFAR and OS-CFAR as output threshold depends on the nearest value with the output of neural network. The neural network used in this research is the Multi-Layer Perceptron (MLP) consisted of two hidden layers. The input of neural network was as many as 3 consisted of CA and OS CFAR and Cell Under Test (CUT) value. The pattern of those inputs will be classified and recognized by the neural network by the training to calculate the preliminary threshold. That threshold will be compared to CA and OS CFAR to select the best final threshold. The method was examined with three simulated common radar cases including homogeneous background, multi target and clutter wall environment. The experiments show that the proposed method is capable to select properly based on the best performance of both CA and OS CFAR in homogeneous and non-homogeneous environments.

Fractional-N PLL Synthesizer for linear FMCW Radar Signal Generator

Radar signal generator is a key component in radar system as it determines the best achievable resolution. This paper presents a realization process, of how a programmable Fractional-N PLL Synthesizer was made suitable as a linear FMCW signal generator for X-band marine radar applications. The realization using HMC769LP6CE PLL with integrated VCO controlled by ATMega328 microcontroller and Altera EPM240T100C5 CPLD discussed in detail. The performance of single chip PLL-VCO architecture with reconfigurable bandwidth capability in real time is measured using passband spectrum. The experimental results indicate that the PLL-VCO architecture is a preferred choice for high-resolution FMCW radar application due to their architectural simplicity.

Narrow-band microwave planar filter using multiple-poled hairpin resonators

A microwave planar filter using multi-poled Hairpin resonators in a Roger substrate is proposed for narrow-band operation in S-band applications. The proposed filter is composed of several pole resonators with Hairpin structures and designed with planar structures on a Roger substrate. 100 MHz bandwidth in 3 GHz operational frequency is designed for the proposed filter. Calculation methods using simulation software and results of the characteristics are discussed and reported. The proposed device is analyzed using Advanced Design System (ADS) software where the substrate with dielectric constant of 3.48 and thickness of 1.524 mm is used. The designed device has a simple and compact structure, easy in design and fabrication, and compatible with integrated microwave circuit.

Summed area table for optimizing of processing time on CA CFAR algorithm

Radar is a system using electromagnetic waves for detecting the existence of an object. The algorithm commonly used is Cell-Averaging (CA-CFAR). The disadvantage of this algorithm is that has high computational time which can influence the detection performance on low end hardware/GPU system that used in low cost radar system. The more complex algorithm will need the longer time to process and the longer delay to display the result of detection. To overcome this problem, we propose summed-area-table technique which has been popular in computer vision community to reduce processing time of algorithm. The CA-CFAR algorithm which is developed with summed area table technique can reduce processing time so that become two times faster than the CA-CFAR algorithm using iterative summation in calculating the average value of background clutter.