SySense (United States)

Sound source localisation is used in many consumer devices, to isolate audio from individual speakers and reject noise. Localization is frequently accomplished by “beamforming”, which combines phase-shifted audio streams to increase power from chosen source directions, under a known microphone array geometry. Dense band-pass filters are often needed to obtain narrowband signal components from wideband audio. These approaches achieve high accuracy, but narrowband beamforming is computationally demanding, and not ideal for low-power IoT devices. We introduce a method for sound source localisation on arbitrary microphone arrays, designed for efficient implementation in ultra-low-power spiking neural networks (SNNs). We use a Hilbert transform to avoid dense band-pass filters, and introduce an event-based encoding method that captures the phase of the complex analytic signal. Our approach achieves high accuracy for SNN methods, comparable with traditional non-SNN super-resolution beamforming. We deploy our method to low-power SNN inference hardware, with much lower power consumption than super-resolution methods. We demonstrate that signal processing approaches co-designed with spiking neural network implementations can achieve much improved power efficiency. Our Hilbert-transform-based method for beamforming can also improve the efficiency of traditional digital signal processing.

The optimal cruise trajectory for a detail designed hypersonic waverider vehicle is determined. Two possible local extrema are found representing the steady state and periodic cruise trajectories. The optimal steady state cruise is determined by minimizing the instantaneous fuel rate per distance subject to the dynamics being in equilibrium. The approximately optimal periodic cruise is determined by minimizing the fuel used over an optimal range period subject to a periodicity condition on the initial and terminal values of the altitude, velocity, and ∞ight path angle, assuming that the vehicle weight is given and held flxed over the range period. It is shown that if a door is placed over the inlet during the power-ofi phase increasing the drag by 50%, but increasing the lift by 35%, the periodic ∞ight over the cruise region is 13.27% better than ∞ying in steady state. Results for mechanizing the periodic ∞ight by a linear guidance rule allow the constant vehicle weight assumption to be removed, but retain the periodic cruise performance.

Two new algorithms for homing missile guidance and estimation in the two-dimensional intercept problem are proposed based on the assumption that certain targets execute evasive maneuvers orthogonal to their velocity vectors. The objectives of both algorithms are to estimate the engagement states in the presence of unknown target accelerations and guide the interceptor to hit the target based on these state estimates. Both algorithms are the integration of a fllter in cascade with a guidance law but constructed using difierent philosophies. One algorithm constructs the fllter that estimates the target acceleration and the guidance law based on a target model in which the magnitude of the target acceleration vector is assumed to be a sinusoidal function. The other algorithm constructs the fllter by blocking the dynamic efiect of the target acceleration and constructs the guidance law based on the anticipated worst possible target acceleration. These two algorithms form an interesting design trade between the inherent estimation lag and increased estimation uncertainty.

The spectral theory underlining the structure of the detection filter is re-examined. First, it is shown that the structures of the detection filter constructed by using the spectral theory and geometric theory are equivalent. Furthermore, the existence of the detection filter gain is shown. Finally, a new algorithm for the detection filter design is derived