Target Detection and Noise Reduction in Radar Systems
이슬람 엠디 사이풀
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Radar is a powerful tool that uses electromagnetic waves for detecting, tracking and measuring the speed of reflecting objects such as aircraft, ships, spacecraft, vehicles, people, weather formations, and terrain by day and night. Early development in the radar was mostly driven by military and the military is still the dominant user and developer of radar technology. However, radar now has a very wide range of applications including meteorological detection of precipitation, air traffic control, measuring ocean surface waves, police detection of speeding traffic, sports radar speed guns, and preventing car or ship collisions. Almost all of the major developments in recent years that have made a significant difference in what radar can accomplish can be attributed to progress made in digital signal processing on received data. Several signal processing techniques can be performed on raw receiver signals. The radar receiver is becoming more and more digital. Some common radar signal processing techniques are correlation, Doppler filtering, image processing, detection processing, and tracking. To perform these signal processing operations, almost all modern radars use digital signal processors. These digital processors are very complex chips, implementing very complex algorithms. The purpose of this thesis is the development and analysis of radar signal processing based on detection and noise reduction. The most fundamental problem in radar signal is the detection of an object or physical phenomenon. In this thesis, the detection decision for targets is proposed using cross-correlation instead of statistical decision theory. The radar types consider in the thesis is a continuous wave radar and Pulse radar. Algorithms give good accuracy about the detection of the targets. Several simulations have been performed to verify the algorithm. Even in the case of 90 percent loss of the transmitted signal, the proposed detection method performs accurately. Then, this thesis compares matched filter and wavelet transform applied to both continuous wave radar and pulse radar signals to reduce the noise. For removing noise and extracting signal, wavelet analysis is one of the most important methods. The de-noising application of the wavelets has been used in spectrum cleaning of the atmospheric radar signals. Matched filter has strong anti-noise ability; it can also achieve accurate pulse compression in a very noisy environment. The simulation results indicate that Matched filter has strong anti-noise ability for Pulse Radar and Wavelet for Continuous Wave Radar.