| In this dissertation, we consider the application of order-based tests for radar constant false alarm rate (CFAR) detector and wireless code division multiple access (CDMA). We evaluated the performances of several distributed CFAR tests operating in different background clutter conditions. The analysis considers the detection of Rayleigh target in various clutters with the possibility of differing clutter power levels in the test cells of distributed radars. Numerical results studied for a two radar system show how the false alarm rate of the maximum order statistic (MOS) test changes with differences in the clutter power levels of the test cells. The analysis for the detection of Rayleigh target in Rayleigh clutter indicates that, with differing test cells' power levels, the OR fusion rule can be quite competitive with the proposed normalized test statistic (NTS). However, for the detection of Rayleigh target in Weibull or K-distributed clutter, the results show that NTS outperforms both the OR and the AND rules under the condition of large signal to clutter power ratio and moderate shape parameter values.; We also analyzed few schemes for combining base station antenna array signals in IS-95 wireless DS/CDMA. The performances of equal gain combining (EGC), likelihood ratio test (LRT) and several rank tests are evaluated using simulation studies. The rank tests studied are the rank sum test (RST), the modified rank test (MRT), and the row sorted modified rank test (RMRT). The results indicate that, under certain assumptions on multiple access interference statistics, the probability of error of RST, MRT, and RMRT are lower than that of EGC, if a few high power interfering users are present along with a low power user of interest. Our study also reveals that the multiple access interference for low number of users is distributed as Laplace and not as Gaussian. If there are a moderately large number of users and if the received power of all the users are nearly the same, then EGC outperforms the rank tests. In fact, under this condition, the performance of EGC is close to that of the optimal likelihood ratio test. |
