International Telemetering Conference Proceedings / October 28-31, 1985 / Riviera Hotel, Las Vegas, Nevada / PSL is developing a telemetry antenna intended to avoid the mechanical complexity of traditional parabolic passive monopulse trackers. For a considerable range of reception scenarios, a stationary non-tracking antenna will fill the reception requirement while greatly simplyfing the antenna hardware as compared to mechanical passive trackers. A single, phi-symmetric, shaped-beam antenna provides proper coverage of the test range for multiple airborne targets. This system is not time shared and requires no acquisition time. Approximate azimuth to the target is displayed on a CRT. This paper examines the applicable test scenario and the resulting hardware.

Time Delay of Arrival (TDOA) based algorithms and Steered Response Power (SRP) based algorithms are two most commonly used methods for sound source detection and localization. SRP is more robust under high reverberation and multi-target conditions, while TDOA is less computationally intensive. This thesis introduces a modified TDOA algorithm, TDOA delay table search (TDOA-DTS), that has more stable performance than the original TDOA, and requires only 4% of the SRP computation load for a 3-dimensional space of a typical room. A 2-step adaptive thresholding procedure based on a Weibull noise peak distributions for the cross-correlations and a binomial distribution for combing potential peaks over all microphone pairs for the final detection. The first threshold limits the potential target peaks in the microphone pair cross-correlations with a user-defined false-alarm (FA) rates. The initial false-positive peak rate can be set to a higher level than desired for the final FA target rate so that high accuracy is not required of the probability distribution model (where model errors do not impact FA rates as they work for threshold set deep into the tail of the curve). The final FA rate can be lowered to the actual desired value using an M out of N (MON) rule on significant correlation peaks from different microphone pairs associated is a point in the space of interest. The algorithm is tested with simulated and real recorded data to verify resulting FA rates are consistent with the user-defined rates down to 10-6.

This thesis presents a novel aspect and polarization invariant electromagnetic target recognition technique in resonance region based on use of MUSIC algorithm for the extraction of natural-resonance related target features. In the suggested method, the feature patterns called &ldquo / MUSIC Spectrum Matrices (MSMs)&rdquo / are constructed for each candidate target at each reference aspect angle using targets&rsquo / scattered data at different late-time intervals. These individual MSMs correspond to maps of targets&rsquo / natural-resonance related power distributions. All these patterns are first used to obtain optimal late-time interval for classifier design and a &ldquo / Fused MUSIC Spectrum Matrix (FMSM)&rdquo / is generated over this interval for each target by superposing MSMs. The resulting FMSMs include more complete information for target resonances and are almost insensitive to aspect and polarization. In case of multiple target recognition, the relative locations of a multi-target group and separation distance between targets are also important factors. Therefore, MSM features are computed for each multi-target group at each &ldquo / reference aspect/topology&rdquo / combination to determine the optimum late-time interval. The FMSM feature of a given multi-target group is obtained by the superposition of all these aspect and topology dependent MSMs. In both single and multiple target recognition cases, the resulting FMSM power patterns are main target features of the designed classifier to be used during real-time decisions. At decision phase, the unknown test target is classified either as one of the candidate targets or as an alien target by comparing correlation coefficients computed between MSM of test signal and FMSM of each candidate target.