FAST ALGORITHM FOR NON-UNIFORMLY SAMPLED SIGNAL SPECTRUM RECONSTRUCTION

In this paper, a fast algorithm to reconstruct the spectrum of non-uniformly sampled signals is proposed. Compared with the original algorithm, the fast algorithm has a higher computational efficiency, especially when sampling sequence is long. Particularly, a transformation matrix is built, and the reconstructed spectrum is perfectly synthesized from the spectrum of every sampling channel. The fast algorithm has solved efficiency issues of spectrum reconstruction algorithm, and making it possible for the actual application of spectrum reconstruction algorithm in multi-channel Synthetic Aperture Radar (SAR).

Reconstruction of energy spectrum of runaway electrons in nanosecond-pulse discharges in atmospheric air

This paper presents an experimental investigation into the runaway electron spectrum with a gas diode composed of a rough spherical cathode and plane anode under the excitation of a nanosecond-pulse generator in atmospheric air.The runaway electron beams are measured by a collector covered with aluminum foil with a thickness from 0μm(mesh grid)to 50μm.The energy spectrum is calculated by an improved Tikhonov regularization called the maximum entropy method.The experimental results show that the transition state of the discharge consisted of multiple streamer channels stretched from the cathode with glow-like plasma uniformly distributed over the anode.The number of runaway electrons measured by the collector is in the order of 1010 in atmospheric pressure air with a gap spacing of 5 mm and applied voltages of70–130 kV.The cathode with a rough surface creates a more inhomogeneous electric field and larger emission site for the runaway electrons around the cathode,providing conditions for the coexistence of filamentary streamer and diffuse discharge.The reconstructed spectra show that the energy distribution of the runaway electrons presents a single-peak profile with energies from eU_(m/2)–2 eU_(m/3)(U_(m)is maximal voltage across the gap).

Compressed sensing reconstruction of sparse spectrum based on digital micro-mirror device platform

A new method which employs compressive sensing(CS) to reconstruct the sparse spectrum is designed and experimentally demonstrated. On the basis of CS theory, the simulation results indicate that the probability of reconstruction is high when the step of the sparsity adaptive matching pursuit algorithm is confirmed as 1. Contrastive analysis for four kinds of commonly used measurement matrices: part Hadamard, Bernoulli, Toeplitz and Circular matrix, has been conducted. The results illustrate that the part Hadamard matrix has better performance of reconstruction than the other matrices. The experimental system of the spectral compression reconstruction is mainly based on the digital micro-mirror device(DMD). The experimental results prove that CS can reconstruct sparse spectrum well under the condition of 50% sampling rate. The system error 0.0781 is obtained, which is defined by the average value of the 2-norm. Furthermore, the proposed method shows a dominant ability to discard redundancy.