Infrared Image Reconstruction Based on Archimedes Spiral Measurement Matrix

It is a new research direction to realize infrared(IR) image reconstruction using compressed sensing(CS) theory. In the field of CS, the construction of measurement matrix is very principal. At present, the types of measurement matrices are mainly random and deterministic. The random measurement matrix can well satisfy the property of measurement matrix, but needs a large amount of storage space and has an inconvenient in hardware implementation. Therefore, a deterministic measurement matrix construction method is proposed for IR image reconstruction in this paper. Firstly, a series of points are collected on Archimedes spiral to construct a definite sequence; then the initial measurement matrix is constructed; finally, the deterministic measurement matrix is obtained according to the required sampling rate. Simulation results show that the IR image could be reconstructed by the measured values obtained through the proposed measurement matrix. Moreover, the proposed measurement matrix has better reconstruction performance compared with the Gaussian and Bernoulli random measurement matrices.     

TDOA Passive Location Based on Cuckoo Search Algorithm

This paper formulates a new framework to estimate the target position by adopting cuckoo search(CS)positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time difference of arrival(TDOA). With the application of the Levy flight mechanism, the preferential selection mechanism and the elimination mechanism, the proposed approach prevents positioning results from falling into local optimum. These intelligent mechanisms are useful to ensure the population diversity and improve the convergence speed. Simulation results demonstrate that the cuckoo localization algorithm has higher locating precision and better performance than the conventional methods. Compared with particle swarm optimization(PSO) algorithm and Newton iteration algorithm, the proposed method can obtain the Cram′er-Rao lower bound(CRLB) and quickly achieve the global optimal solutions.