APB-1 Consumer Reports Addendum: Beam Noise Predictions for the MVSC Adaptive Beamformer
This report completes the Consumer Reports performance analysis study for the Phase 1 Advanced Processor Build sonar system. It provides a performance comparison between the conventional beamformer and the beam-based minimum variance soft constraint adaptive beamformer processing modules. Comparison was based on a beam noise output metric defined in terms of the beamformer array gain. This provides a more realistic measure of beamformer performance since, unlike the common definition of beam noise based solely on the noise field input to the beamformer, our beam noise metric factors in changes of signal power as the target signal is passed through the beamformer. Our results indicate that performance gain can be realized for the adaptive beamformer for certain scenarios. These gains were most likely to occur at the medium frequencies between 100 and 200 Hz, while significant gain was only occasionally observed at other frequencies. Adaptive beamforming was particularly successful when a clutter signal was present. However, any performance advantage usually begins to disappear as the target signal-to-noise ratio increases above approximately –15 dB.
Array Gain as a Function of SNR for the Beam-based MVSC Adaptive Beamformer
This paper examines the beam-based minimum variance soft constraint beamformer and shows that the beamformer array gain is almost always a function of SNR. The analysis shows that the MVSC array gain is necessarily a nonincreasing function of SNR and, in fact, is either strictly decreasing or constant relative to SNR. This result supplements earlier results of Van Veen and helps explain behavior observed in processed data.
Training and maintaining the performance of dogs (Canis familiaris) on an increasing number of odor discriminations in a controlled setting
Abstract The number of substances detector dogs are trained to detect varies depending on the mission of the agency they serve. No studies have been conducted concerning how training multiple odor discriminations affects detection performance and refresher training requirements. This study used a controlled field setting to examine the effects of training dogs to detect multiple substances on their subsequent detection performance and refresher training requirements. Dogs were first trained to detect a single odor. Their detection performance was tested 10 days later and refresher training was then given to bring their performance back up to a predetermined standard. Following refresher training, detection of a new substance was trained, and approximately 10 days later the detection of both trained substances was tested. This sequence of testing, refresher training, and new odor training continued every 10 days until the dogs had been trained and tested on 10 odors. The detection of previously learned odors did not decrease as the number of substances trained increased. In fact, the amount of training required to refresh detection performance and to train new odor discriminations tended to decrease as more odor discriminations were trained.