Although the computational complexity of the EFA and JDL algorithms is lower than our proposed LRGP KA-STAP algorithm, two aspects should be noted.
In Figures 3(a), 3(b), and 3(c), we show the SINR performance against the target Doppler frequency of our proposed LRGP KA-STAP algorithm both with and without a CMT.
The plots show that the proposed LRGP KA-STAP algorithm without a CMT is sensitive to the velocity misalignment, while the LRGP KA-STAP algorithm with a CMT is robust to that.
The curves also indicate that (i) the proposed LRGP KA-STAP algorithm without a CMT is sensitive to the yaw angle misalignment, while the LRGP KA-STAP algorithm with a CMT is robust to that; (ii) a slightly larger value of the estimated parameter [[sigma].sub.v] will result in an improved SINR performance.
To provide further investigation about the performance of our proposed algorithms, we compare the SINR performance versus the snapshots of our proposed LRGP KA-STAP and LRGP RD-KA-STAP algorithms with the Loaded SMI (LSMI), the EFA algorithm (3 Doppler bins), the 3 x 3JDL algorithm, Stoica's scheme in  (the prior knowledge covariance matrix is computed in the same way as the CSMIECC algorithm), and the CSMIECC algorithm (the combination parameter is set to 0.6) in , where the simulation results are shown in Figure 6.
It is found that our proposed LRGP KA-STAP algorithm provides the best SINR performance among all algorithms and forms the narrowest clutter null resulting in improved performance for the detection of slow targets.