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Interference is a key factor in radar return misdetection. Strong interference might make it difficult to detect the signal or targets. When interference occurs in the sidelobes of the antenna pattern, Sidelobe Cancellation (SLC) and Sidelobe Blanking are two unique solutions to solve this problem (SLB). Aside from this approach, the probability of false alert and likelihood of detection are the most essential parameters in radar. The chance of a false alarm for any radar system should be minimal, and as a result, the probability of detection should be high. There are several interference cancellation strategies in the literature that are used to sustain consistent false alarms regardless of the clutter environment. With the necessity for interference cancellation methods and the constant false alarm rate (CFAR), the Maisel SLC algorithm has been modified to create a new algorithm for recognizing targets in the presence of severe interference. The received radar returns and interference are simulated as non-stationary in this approach, and sidelobe interference is cancelled using an adaptive algorithm. By comparing the performance of adaptive algorithms, simulation results are shown. In a severe clutter situation, the simulation results demonstrate a considerable increase in target recognition and signal to noise ratio when compared to the previous technique.

Modeling Target Detection and Performance Analysis of Electronic Countermeasures for Phased Radar