There are not adequate independent and identically distributed training samples under a heterogeneous clutter environment.Thus
this paper proposes a knowledge-aided LCMV-STAP approach.Firstly
the weight of knowledge-aided LCMV-STAP model is solved
and then the formula of the relationship between the color loading factors and the constraint constants is derived.Finally
the two color loading factors are solved.The computer simulations show that knowledge-aided LCMV-STAP has a better output signal-interference noise ratio than the traditional approach under a heterogeneous clutter environment
and the detection probability of Adaptive Matched Filter is higher than that of the traditional approach.