KEYWORDS: Tunable filters, Detection and tracking algorithms, Electronic filtering, Signal detection, Environmental sensing, Digital filtering, Signal to noise ratio, Target detection, Clutter, Mathematical optimization
Constant false alarm detection plays an important role in radar communication imaging technology. The doped noise in the signal is one of the main reasons affecting the detection efficiency of constant false alarm, and the filtering algorithm can remove the noise and improve the detection performance. Most of the existing filtering algorithms have good filtering effect only for the noise in a specific environment. In this paper, a universal adaptive filtering selection algorithm is proposed by combining the adaptive filtering algorithm and the classical mean-class constant false alarm algorithm, which can improve the detection probability under different background noises. Finally, simulation experiments are given to verify that the adaptive filter selection algorithm proposed in this paper can be selected for different environments, and can maintain a better detection probability of mean class constant false alarm than other existing single algorithms.
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