Moving Target Detection in Multichannel SAR Framework Using Adaptive Neuro Fuzzy Decisive Technique
Eppili Jaya1, B.T. Krishna2
1Eppili Jaya, Ph. D Scholar, Engineering and Communication Engineering, JNTUK University, Kakinada, (A.P.), India and Department of Engineering and Communication Engineering, Aditya Institute of Technology and management, Tekkali, India.
2B.T. Krishna, Department of Engineering and Communication Engineering, JNTUK University, Kakinada, (A.P.), India
Manuscript received on 11 March 2019 | Revised Manuscript received on 17 March 2019 | Manuscript published on 30 July 2019 | PP: 4517-4523 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3682078219/19©BEIESP | DOI: 10.35940/ijrte.B3682.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Precise and efficacious detection of moving targets is a prominent task in on-going synthetic aperture radar (SAR) technique. The perception of moving object allows quite significant data about the situation under observation for both surveillance and intelligence activities. The task of accurately locating moving targets against strong background clutter in minimum of time is of utmost interest in the current research area. Fractional Fourier Transform (FrFT) concentrates the energy of the required chirp signal so that it can be well separated from the chirp like noise. The proposed SAR Moving Target Detection (MTD) process is based on the combination of FrFT with the adaptive-neuro fuzzy decisive technique. The correlation among the received signal and the FrFT of the received signal are computed which maximizes the required signal energy and applied to the adaptive-neuro fuzzy decisive module that detects the target location adaptively using the fuzzy linguistic rules. The simulation is performed by changing the number of targets, different Pulse repetition intervals, antenna turn velocity, iterations and the analysis is carried out based on the metrics, like detection time, missed target rate, and Mean Square Error (MSE), proving that the proposed Adaptive-Neuro Fuzzy-based MTD process detected the object in 5.0237 secs with a minimum missed target rate of 0.1210 and MSE of 23377.48.
Index Terms: Adaptive-Neuro Fuzzy MTD, Multichannel SAR, FrFT, Correlation, Ambiguity Function
Scope of the Article: Fuzzy Logics