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This paper presents an important improvement on Sherman's method for angle estimation of two unresolved targets when using monopulse radar. The graphical or numerical solution for the 6th-order polynomial equation is replaced with a quadratic equation that has exact algebraic solutions for nonfluctuating or slowly fluctuating targets. The proposed method can also estimate the angle for a single target without ambiguity and can estimate the angles when two targets are positioned at the same azimuth or elevation angle, in contrast with previous techniques. The proposed method is validated using simulations.

Abstract-This paper proposes a fusion technique of feature vectors that improves the performance of radar target recognition. The proposed method utilizes more information than simple monostatic or bistatic (single receiver) algorithms by combining extracted feature vectors from multiple (two or three) receivers. In order to verify the performance of the proposed method, we use the calculated monostatic and bistatic RCS of three full-scale aircraft and the measured monotatic and bistatic RCS of four scalemodel targets. The scattering centers are extracted using one-dimensional FFT-based CLEAN and then used as feature vectors for a neural network classifier. The results show that our method has better performance than algorithms that solely use monostatic or bistatic data.

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