Compressive sensing, a newly emerging method from information technology, is applied to array beamforming and associated acoustic applications. A compressive sensing beamforming method (CSB-II) is developed based on sampling covariance matrix, assuming spatially sparse and incoherent signals, and then examined using both simulations and aeroacoustic measurements. The simulation results clearly show that the proposed CSB-II method is robust to sensing noise. In addition, aeroacoustic tests of a landing gear model demonstrate the good performance in terms of resolution and sidelobe rejection.

The experimental method employed in an anechoic wind tunnel to characterize flow-induced noise of the pigeon (Columba livia) during level flight is described in this letter. A live pigeon was managed to maintain a steady level flight at the wind tunnel test flow of 15 m/s. A microphone array was fabricated, and the conventional beamforming method was then adopted to yield the corresponding narrowband acoustic images and broadband sound pressure spectral results. The results justified the experimental method developed in this work. It can be seen that the flight noise of the pigeon is mostly from the wing tips. In addition, the spectral waveform of the pigeon flight suggests a slope of -20 dB/dec between 500 Hz and 5 kHz.

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Two recent test failures of Hypersonic Technology Vehicle 2 impose a strike to the increasingly growing enthusiasm, not only on the United States side. It is important to find out the exact failure reason, otherwise a solution is impossible. In this Note, we propose a potential failure reason from the perspective of lateral stability analysis. We argue that the time variant pressure fluctuations, which are normally omitted in classical aircraft dynamics analysis, could not be neglected in dynamic analysis of hypersonic vehicles. To demonstrate the idea, a hypersonic model is imagined in this work and its aerodynamic parameters are estimated using fundamental fluid principles. Pressure fluctuations are thereafter estimated by an empirical formula. A lateral dynamic equation is set up, taking those time variant fluctuations into account. The resulted equation is a Mathieu differential equation. Numerical solutions of this equation show that the inclusion of fluctuation terms generates more complicated dynamics and should be considered in flight controller design.pitch, yaw momentum coefficients I = moment of inertia, kg · m 2 l = the wing span, m L = roll moment, N · m M = Mach number m = mass of aircraft, kg N = yaw moment, N · m (p, q, r) = roll, pitch and yaw rate, rad/s p rms = rms fluctuating pressure, Pā q = dynamic pressure, Pa S = aerodynamic surface area, m 2 (x, y, z) = coordinates, m V = speed of freestream, m/s α = angle of attack, deg β = angle of sideslip, deg (ϕ, θ) = Euler angles, deg ρ = density of air, kg/m 3 Subscripts e = properties local to aerodynamic shape f = time variant part ∞ = freestream conditions 0 = stationary parts