Low Sidelobe Phased Array Antenna Error Analysis And Compensation Method Research

Antenna sidelobe level is extremely important in phased array antenna system. The phased array antenna sidelobe characteristics largely determine the radar anti-jamming, anti-radiation missiles and clutter suppression, antenna sidelobe become an important indicator of the radar system. Phased array antenna will emerge a variety of errors affect the antenna sidelobe in design and manufacturing process. The error analysis has become the design of phased array antennas to study the problem.Antenna aperture amplitude distribution can control the antenna sidelobe, but the introduction of error makes the antenna sidelobe level lifted. This paper analyzes the impact of random errors on the antenna sidelobe. The subarray amplitude tapering causes the split of the beams, the phase quantization error caused to produce a high parasitic lobe level and given a compensation method.The paper gives relationship between the random amplitude and phase errors It analysis sidelobe level changes caused by the random error. When the variance of the random amplitude and phase errors stand in a value, the actual sidelobe level exceed the probability of accumulation of design sidelobe level, in order to meet the demand, the designer must devise the lower antenna sidelobe level.The paper analysis the subarray amplitude, amplitude tapering makes the beam broadening and form the split of the beams on the angle of the grating lobes. In order not to increase the complexity of the feed network and reduce the effect of the phased array antenna sidelobe. The element coefficient combining the subarray amplitude weighting and the same serial number in the subarray element get the approximate ideal weight.This paper focuses on the phase quantization error caused by the digital phase shifter, the number of bits of digital phase shifter, the number of antenna elements and antenna aperture affected phased array antenna sidelobe and given simulation. Traditional random phase method is used and the simulation results using phase added method and two-probable value method has been given here. The modified random phasing techniques are applied in reducing the parasite lobes level in order to improve performance, Use the Monte Carlo method to compare the appropriate two probable value technique and two probable value technique. Compare some different c the probability of the peak sidelobe level. The optimal result being a statistical average, phase feedback is random and difference. In this paper, the Adaptive Genetic Algorithm (AGA) is applied to optimize the appropriate two probable value technique and effectively suppress the parasitic lobes. It is better than the traditional genetic algorithm optimization results, The simulation results reveal that the adaptive genetic algorithm can obtain steady and optimal phase distribution for the phased array antenna.