Design of Frequency Invariant Wideband Beamformer with Real and Symmetric FIR Filters

An approach to wideband beamformer with frequency invariant property is proposed by optimising the space-time two-dimensional finite impulse response (FIR) filters. Frequency invariant beam pattern brings some restrictions on frequency bandwith and filter length. Using the Landau-Pollak theorem to estimate the rank of wideband signals, we give the lower bound of filter length respect to array element numbers and the relative bandwidth of wideband signal. With the expression of beam pattern using real and symmetric FIR filters, we develop corresponding optimisation formation considering the robustness of beamformer as well, which can be easily solved by the least mean square (LMS) algorithm. A design example is provided to show the effectiveness of the proposed method.Defence Science Journal, 2012, 62(4), pp.243-247, DOI:http://dx.doi.org/10.14429/dsj.62.96

A Novel Technique Based on the Combination of Labeled Co-Occurrence Matrix and Variogram for the Detection of Built-up Areas in High-Resolution SAR Images

Interests in synthetic aperture radar (SAR) data analysis is driven by the constantly increased spatial resolutions of the acquired images, where the geometries of scene objects can be better defined than in lower resolution data. This paper addresses the problem of the built-up areas extraction in high-resolution (HR) SAR images, which can provide a wealth of information to characterize urban environments. Strong backscattering behavior is one of the distinct characteristics of built-up areas in a SAR image. However, in practical applications, only a small portion of pixels characterizing the built-up areas appears bright. Thus, specific texture measures should be considered for identifying these areas. This paper presents a novel texture measure by combining the proposed labeled co-occurrence matrix technique with the specific spatial variability structure of the considered land-cover type in the fuzzy set theory. The spatial variability is analyzed by means of variogram, which reflects the spatial correlation or non-similarity associated with a particular terrain surface. The derived parameters from the variograms are used to establish fuzzy functions to characterize the built-up class and non built-up class, separately. The proposed technique was tested on TerraSAR-X images acquired of Nanjing (China) and Barcelona (Spain), and on a COSMO-SkyMed image acquired of Hangzhou (China). The obtained classification accuracies point out the effectiveness of the proposed technique in identifying and detecting built-up areas

A Real-time Target Detection Algorithm for Panorama Infrared Search and Track System

AbstractWith regard to target detection in high resolution panorama images attained by circumferential scan Infrared Search and Tracking system, a rough-to-meticulous real-time target detection algorithm is proposed based on analysis of characteristics of targets and background. In the rough detection phase, it attains initial high rate target detection by quick real-time algorithm, based on the gray high frequency and movement characteristics of the target in the whole panorama image. In the meticulous detection phase, focusing on the detected suspected target sliced images, it has further delicate detection and recognition on the basis of targets’ characteristics to exclude those false jamming. The detection result of the test images shows, the algorithm enables stable detection with low-rate false alarm for distant dim small targets, and has been applied to the development of engineering sample of the Panorama Infrared Search and Tracking system

Microsoft Word - 8278 Tamplate.

Abstract: With the developments of network communication, electronic commerce plays a more and more role in the trade business and industry structure. The requirement for the electronic commerce turns to be higher. In this study, we study current status about the cryptographic algorithms exploited in electronic commerce. We discuss the advantages and disadvantages about the symmetric and asymmetric algorithms and improve them. Then we give a new scheme that combines the improved symmetric algorithm and asymmetric algorithm. We give sound reasons to explain why our scheme is more secure. Finally, we carry the experiments to show the security of our scheme

Weak Target Detection Method of Passive Bistatic Radar Based on Probability Histogram

Passive bistatic radar (PBR) has attracted widespread attention for its capabilities in dealing with the threat of electronic countermeasure, stealth technology, and antiradiation missile. However, passive detection methods are limited by unknown characteristics of the uncooperative illuminators, and conventional radar signal processing algorithms cannot be conducted accurately, especially when the carrier frequency of the transmitting signal is agile and the signal-to-noise ratio (SNR) in the scattered wave of target is low. To address the above problems, this paper presents a novel weak target detection method based on probability histogram, which is then tested by a field experiment. Preliminary results indicate the feasibility of the proposed method in weak target detection

Refined PHD Filter for Multi-Target Tracking under Low Detection Probability

Radar target detection probability will decrease as the target echo signal-to-noise ratio (SNR) decreases, which has an adverse influence on the result of multi-target tracking. The performances of standard multi-target tracking algorithms degrade significantly under low detection probability in practice, especially when continuous miss detection occurs. Based on sequential Monte Carlo implementation of Probability Hypothesis Density (PHD) filter, this paper proposes a heuristic method called the Refined PHD (R-PHD) filter to improve multi-target tracking performance under low detection probability. In detail, this paper defines a survival probability which is dependent on target state, and labels individual extracted targets and corresponding particles. When miss detection occurs due to low detection probability, posterior particle weights will be revised according to the prediction step. Finally, we transform the target confirmation problem into a hypothesis test problem, and utilize sequential probability ratio test to distinguish real targets and false alarms in real time. Computer simulations with respect to different detection probabilities, average numbers of false alarms and continuous miss detection durations are provided to corroborate the superiority of the proposed method, compared with standard PHD filter, Cardinalized PHD (CPHD) filter and Cardinality Balanced Multi-target Multi-Bernoulli (CBMeMBer) filter

Parameter Estimation of SAR Signal Based on SVD for the Nyquist Folding Receiver

The Nyquist Folding Receiver (NYFR) is a novel ultra-wideband (UWB) receiver structure that can realize wideband signal monitoring with fewer components. The NYFR induces a Nyquist zone (NZ)-dependent sinusoidal frequency modulation (SFM) by a modulated local oscillator (LOS), and the intercepted linear frequency modulated (LFM) synthetic aperture radar (SAR) signal will be converted into an LFM/SFM hybrid modulated signal. In this paper, a parameter estimation algorithm is proposed for the complicated NYFR output signal. According to the NYFR prior information, a chirp singular value ratio (CSVR) spectrum method based on singular value decomposition (SVD) is proposed to estimate the chirp rate directly before estimating the NZ index. Then, a fast search algorithm based on golden section method for the CSVR spectrum is analyzed, which can obviously reduce the computational complexity. The simulation shows that the presented algorithm can accurately estimate the parameters of the LFM/SFM hybrid modulated output signal by the NYFR