M-Sweeps multi-target analysis of new category of adaptive schemes for detecting χ2-fluctuating targets

Abstract

With the technology of clutter excitation developing up, adaptive processing algorithms have become critical in high performance radar systems. Target echoes can be obscured and false alarms can occur in the presence of such type of interference. This clutter can be mitigated by appropriate strategy of adaptive processors, in which the false alarm rate holds constant (CFAR) by providing a detection threshold of definite value above clutter. Therefore, the CFAR mechanism becomes an indispensable technique for fluctuating target detection; especially in heterogeneous environments. There are many scenarios to achieve such indigence property. However, difficulties in finding a single procedure to deal with diverse noise backgrounds are the prime thrust for developing a new structure based on composite architecture. In this regard, fusion of cell-averaging (CA), order-statistics (OS) and trimmed-mean (TM) strategies within fusion adaptive detectors results in higher detection performance. This paper is devoted to the analysis of this new model in the case where the radar receiver is supplemented by a non-coherent integrator of M-pulses. The tested as well as the spurious targets are assumed to follow χ2-distribution with two degrees of freedom in their fluctuation. Closed-form expression is derived for the detection performance. Our simulation results illustrate the significant advantage of the new model in both homogeneous and multi-target performances. In ideal situation, its performance outweighs that of the classical Neyman-Pearson (N-P) detector which is commonly regarded as the reference model for comparing new implementations in the CFAR world.

Keywords

• cfar processors
• clutter and interference
• derived detectors
• χ2-distribution
• swerling models
• swi & swii
• non-coherent integration of m pulses
• target multiplicity environments