The key issue of the subspace-based Direction Of Arrival (DOA) estimation lies in the estimation of signal subspace with high quality. In the case of uncorrelated signals while the signals are temporally correlated ones, a novel approach for estimation of DOA in unknown correlated noise fields is proposed. Based on the biorthogonality between a matrix and its Moore-Penrose pseudo-inverse, the proposed method makes no assumptions on the spatial covariance matrix of the noise. The approach exploits the structural information of a set of spatio-temporal correlation matrices, and gives a robust and precise estimation of signal subspace to obtain a precise estimation of DOA. The performances are confirmed by computer simulation results.

A novel algorithm both for restraining intensive interferences and for estimating weak signals' DOA(Direction Of Arrival) information is presented on the basis of uniform linear array. Under the assumption knowing the number and directions of intensive interferences, first, the algorithm forms the beam on the sub-array level with the improved beam-forming method to constrain interferences; then, the algorithm estimates weak signals' DOA information based on all of these weighed sub-arrays. When both the desired signal and the interference are in the same beam, the merit of this algorithm shows higher estimation accuracy than that of high-resolution methods without improving the SNR for weak signal. Both the theoretical analysis and computer simulation indicate that the algorithm is effective.

Combining the Multiple Linear Constraint (MLC)minimal variance criterion and maximal SNR criterion, the maximal SNR beamformer is proposed with Multiple Linear Constraint to Determine. (MLCD)The maximal SINR is obtained to evaluating the filtering performance. The optimal weighted vector is presented according to the optimal gain vector of desired signals. The filtering performance is improved greatly contrasting to the multiple linear constraint minimal variance beamformer.

Following a brief discussion on basic LMS algorithms, the ELMS algorithms with steady small MSE is introduced. The new algorithm using the adaptive NLMS signal-estimator to predict the signal s(k). Forgetting factor λ_i and error signal are used to control the step size update for iteration. Theoretics analysi and computer simulations demonstrate that the presented algorithm has good performance both in convergence properties and steady small misadjustment.

The research purpose of this paper is to estimate the parameter vector (β, σ²,σ²_w)of (1/f)-type fractal stochastic processes. Using wavelets, the paper has performed a series of algebraic operation to the variance of the observation wavelet coefficients of process, and presented the elaborate theoretical analysis. As a result, the parameter vector of fractional Brownian motions (fBm) in noise is introduced. The experimental results demonstrate that the new estimator is far simpler and more effective than the traditional ML estimator and the range of estimate parameter is wider. Moreover the distribution of noise is not restricted within Gauss processes.

An Algorithm Of Constant Modulus Signal Separation based on Minimal Rayleigh Entropy (MRE-AOCMSS) is presented. Utilizing an error cost function,a novel covariance matrix is constructed. Then an optimal weight vector used to extract the desired constant modulus signal is obtained via minimizing the Rayleigh entropy. Employing the algorithm, interferences can be cancelled effectively. The algorithm is still valid when co-channel interference signal's power is much greater than the desired signal's power. The simulation results indicate that this MRE-AOCMSS algorithm is effective in terms of constant modulus signal separation and interference suppression.

A kind of Dual-mode Constant Modulus Algorithm(DCMA) based on fractionally-spaced equalization for blind equalization is presented to compensate the defects of the Constant Modulus Algorithm(CMA) and the Signed-Regressor CMA(SR-CMA). DCMA combines the conventional CMA and SR-CMA, and the switch process between CMA and SR-CMA is realized by decision circle ring which boundary is decided by the signal-to-noise radio. Computer simulation proves that DCMA is more robust than SR-CMA and more computationally efficient than CMA, and its residual mean-square error is lower than that of CMA and SR-CMA.

A estimator of the time-varying Markov state transition probabilities is presented , which is based on the measurements. Then the Parameter Adaptive Interacting Multiple Model (PAIMM) is designed by adopting the above estimator. In comparison with that of the conventional IMM algorithm , the tracking performance of PAIMM is better in the simulation of tracking a maneuvering target.

On the basis of the limitation of Farid’s universal blind steganalysis for color images, a new universal blind steganalysis scheme is proposed. In view of the luminance and the chrominance of the image, the class feature vector is extracted. A new approach is presented to extract the feature for the chrominance component that the image is directional processed using the vector directional filter, and then the vector direction correlation between the image and its directional filtered image is calculated. It reduces the number of the features enormously, and overcomes the fault of Farid’s scheme that neglects the inherent correlation between the RGB channels, which is propitious to simplify the design of classifier and to improve the performance of the classifier. Applying the scheme and Farid’s scheme to detecting the stego images produced by JSteg, F5, and EZStego respectively, the comparison of these simulation results shows that the scheme is quite more efficient for different size of messages embedded.

A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the existing algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from single-image to image-sequences. Thus the segmentation of multiple objects from complex background and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction.

A new method for two-dimensional super-resolution imaging of radar target in colored Gaussian noise, called two-dimensional FOMC (Fourth-Order Mixed Cumulants) based ESPRIT (2d-FOMCESPRIT) , is presented in this paper. The image is improved for the FOMC could eliminate the Gaussian noise automatically. Additionally this method is computationally much less intensive by holding the dimensions of the feature matrix in the presence of long records. Simulation results show that this method has better image quality than other methods.

This paper provides a ground moving target detection algorithm in Range-Doppler domain with Along-Track Interferometry(ATI) for dual channels SAR after studying ATI theory deeply. It describes the procedure of detection in detail and analyzes the effect of Signal-Noise-Ratio(SNR), Signal-Clutter-Ratio(SCR) and moving target’s velocity. Finally, some typical computer simulation results are presented. Comparing with routine method, the method in the paper requires lower SCR of moving target, and can detects targets both in and out of the clutter main lobe frequency. In addition, it needn’t compress echoes in azimuth, so the computation decreases.

Such factors as complicated spaceborne SAR orbital motion, earth rotation, earth surface curvature etc. make the realization of spaceborne SAR/GMTI different from airborne SAR/GMTI. In this paper, the property of three-antenna spaceborne SAR is analyzed firstly, and then the method of airborne SAR/GMTI processing is given and analyzed. On the basis of airborne SAR/GMTI, an algorithm of spaceborne SAR moving target detection, radial velocity estimation and relocation based on DPCA technique is presented. Finally, spaceborne SAR/GMTI computer simulation results validate its effectiveness.

A fundamental constraint in Synthetic Aperture Radar(SAR) designing is the contradiction between swath width and azimuth resolution. Single phase center multiple beams technique can alleviate the contradiction in some extent and is one of solutions to implement high resolution wide swath spaceborne synthetic aperture radar systems. In this paper, based on the introduction to the principle of single phase center multiple beams technique, the origin of azimuth ambiguities of single phase center multi-beam synthetic aperture radar is analyzed and the formula to compute azimuth ambiguities is presented. Then a simulation example of computing azimuth ambiguities of single phase center multi-beam synthetic aperture radar is given. The results of the paper can be reference for designing single phase center multi-beam synthetic aperture radar systems.

This paper proposes a new algorithm of detecting target with constant acceleration along parabolic track on the radar coordinate plane. This algorithm combines coordinate transformation of the parabolic equation and three-point detection algorithm based on randomized hough transform to detect parabolic tracks in any orientation, and employs the velocity information of detected tracks to delete false alarms. Monte Carlo simulation shows that higher detection probability goes with higher false alarm probability in the background of heavy clutters; however in the background of sparse clutters, the detection performance is better.

Presently the development of researches on the calibration of Pol-InSAR at the stage of the theory and test. There are many limits in the current algorithm. A new improved algorithm is set up with using the sensitivity equation based on the analysis of the errors source. The algorithm get the parameter value by the iterative method based on the sensitivity equation. The algorithm not only improves the precision but also overcome the flaw of homogeneous flat model, reducing the limit condition. By the simulation experiments, it has been proved that the performances of the new improved algorithm is better than the conventional algorithm.

The paper presents a novel stagger MTI filter design algorithm, which can detect weak targets of slow speed out of multi-mode clutters. The method is carried out by slipping pulses, and the best pulse repetitive frequencies selected by gradient-GA make the first notch as shallow as possible, so the weak targets in the first notch can be detected. Multi-model clutters can be suppressed by MTI filter, and blind-velocity can be appeared out of three times velocity of sound. Combined GA’s the capability of the whole searching and not limited by selection of initial parameter with the gradient GA’s advantage of fast searching, it can offer fewer initial population and low computation complexity. The simulation and performance analysis demonstrate the feasibility and validity of the algorithm.

The frequency measurement for dual signals is crucial in radar signal processing. A method, which realizes the fast frequency measurement for dual sinusoidal signals basing on DFT and autocorrelation theory, is given. Firstly, one frequency and its amplitude are determined by DFT, with which to demodulate the signals and eliminate the corresponding component. Then, the gap of the two frequencies is estimated using the autocorrelation theory. Computer simulation confirms that the method is of high precision and fast frequency measurement.

Band selection from multispectral or hyperspectral image data is an effective method to remove redundancy among bands and thus reduce dimension. An efficient algorithm using divergence based class-within principal component analysis (PCA) and analysis of corresponding coefficients is proposed. At first, the covariance of each class is diagonalized through PCA transforms on class data respectively, and then the divergence only depends on the summation of individual feature separability of transformed bands. Secondly, after an analysis of corresponding PCA transform coefficients, the candidate bands, original bands essential to classification, are determined by majority vote. At last, the final band subset is obtained by analyzing the dependency and divergence of bands in every subset generated according to the correlations of original band in candidates. Compared with sequential forward selection, the proposed method reduces the computation complexity, and encouraging results have been shown by experiments with an Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) data set.

A novel system model using a non-binary Turbo concatenated codes is proposed based on analysis about the decoding algorithm of the non-binary Turbo codes in this paper. A shorted RS code(204,188)as outer code and a non-binary Turbo code as a inner code is separated in the system , Symbol-by-Symbol Log-MAP and SOVA algorithm is used in decoding the non-binary Turbo code .The conclusion by simulating is that proposed system has the features of low bit error ratio, low latency and high spectral, etc, compared to the other concatenated codes systems.

Etzion defined and studied the depth spectrums of linear codes on field F_q. In this correspondence, the depth spectrums of linear codes and linear cyclic codes on ring Z₄ are studied, and it is proved that the depth spectrum of linear code of type 4^k₁2^k₂ has at least k₁+k₂ nonzero values, and the depth spectrum of linear cyclic code of type 4^k is {n,n-1,… ,n-k+1} .

In this paper, an approach of eigen-analysis for DS-SS signals under narrow band (multiple tone) interference is proposed, which can estimate the PN (Pseudo Noise) sequence blindly in the low SNR(Signal Noise Ratio) and SIR(Signal Interference Ratio) DS-SS signals. Of course, the parameters of the DS-SS signals (such as period and chip interval of the PN sequence) need to be known. Firstly, the received signal is divided into a lot of non-overlapping temporal vectors according to the period of PN sequence, and then the correlation matrix of the vectors is calculated and accumulated. The eigenvalue decomposition of the matrixes can be computed and the narrow band interference waveforms and the PN sequences of the received signals from the main component eigenvectors can be blindly estimated in the end. Based on the estimated narrow band interference waveforms and PN sequences, the narrow band interference can be rejected, and the DS-SS signals despreading without the PN code can be realized too. Theoretic analysis and experimental results show that the approach is very effective. It can work well on the lower SNR and SIR ambient.

Multiuser detection is a key technique in DS CDMA systems. The received signal of uplink receiver is superposition of the spreading signal transmitted by users over asynchronous channels. Many multiuser detectors deal with discrete signal sampled at symbol or chip rate after passing through matched filterers. However, different relative delay between users results in distinct partial correlation coefficients thus bringing about distinct performance of multiuser detectors. It is very important to effectively evaluate the average and extreme performance of system. In this paper, the expression of average partial correlation coefficients is analyzed and the corresponding numerical computation method is proposed. On the other hand, relative delay corresponding to the maximal and minimal correlation coefficients is also solved by the evolution algorithm. Based on the obtained results, the performance of the decorrelating and Minimum Mean Square Error (MMSE) multiuser detectors in asynchronous DS-CDMA systems are evaluated by numerical simulation.

A Pre-processing Decision-FeedBack Least Squares Constant Modulus blind multiuser detection Algorithm (P-DFB-LSCMA) using antenna arrays is proposed in this paper. It pre-processes the received signals from the antenna arrays and utilizes the least squares constant modulus algorithm based on decision feedback to detection the DS-CDMA signals. Simulation results show that the proposed P-DFB-LSCMA algorithm is superior to DFB-LSCMA and LSCMA, especially with low SNR.

V-BLAST receiver is effective technique in achieving high data rate in wireless communications. However, the complexity of V-BLAST is very high because much time must be consumed in performing linear nulling, successive interference canceling and sorting, and the application of V-BLAST is limited. The complexity of the ZF receiver and MMSE receiver is low, but performance is worse than V-BLAST. In this paper, a new layered space-time receiver is proposed using two stage successive interference canceling, and the complexity of new scheme is very low compared with the V-BLAST. The simulation results indicate that the performance of the proposed receiver based on MMSE is outperforms ZF V-BLAST receiver.

A new differential unitary space-time modulation scheme based on cyclic unitary group code is proposed for systems with multiple transmit antennas in fast fading channels. By exchanging the sequence of transmitted symbols, this new differential unitary space-time modulation scheme reduces the influence from time-variance of fast fading channels at the cost of larger processing delay and additional transmission power. For larger processing delay, the additional transmission power is negligible. Theoretical analysis and Monte Carlo simulations using matlab are carried out to investigate the performance of the conventional and the proposed differential unitary space-time modulation schemes. It is demonstrated that this new differential unitary space-time modulation scheme can achieve significant gains compared with the conventional differential unitary space-time modulation in fast fading channels with very little cost.

In this paper, a novel synchronization algorithm is proposed for OFDM based system in multipath fading channels. In order to mitigate the effect of the multipath, the length of the correlation window is adapted according to the channel maximum time delay estimated in the fore frame. And the further fine synchronization is completed using the multipath information estimated in current frame. Simulation results demonstrate that the synchronization performances are improved greatly compared with the conventional methods. And the method is much suitable for the OFDM time synchronization in multipath fading channel environment.

There exist Inter-Carrier Interference (ICI) phenomena when OFDM signals are transmitted through time-varying fading channels. The performance of communication systems also decreases. Based on decomposing of time-varying fading channels, the system can be treated as data transmitting through a discrete-time white noise filter model channel. The Viterbi algorithm is used to receive the signal. In this way, the ICI and “error floor” in traditional OFDM system are removed, and the performance is enhanced.

Scarcity of the spectrum resource and mobility of users make Quality-of-Service(QoS) provision a critical issue in wireless networks. This paper presents a fuzzy call admission control scheme to meet the requirement of QoS. It searches automatically the optimal number of the guard channels in a base station to make an effective use of resource and guarantee the QoS provision. Simulation compares the proposed fuzzy scheme with a dynamic channel reservation scheme. Simulation results show fuzzy scheme has a better robust performance. It outperforms the adaptive scheme in terms of call dropping probability, call blocking probability, and channel utilization.

In this paper, an attack scheme based on probabilistic cloning machine is proposed, where the eavesdropper measures the quantum state from sender with a probabilitstic cloning machine, and resends the receiver a new result. It is shown that there is still an asymptotic perfect security of quantum key distribution under this attack strategy. The simulation results on classical computer are consistent with the theoretic ones.

In this paper，based on various methods of using extrinsic information, two logarithmic iterative decoding algorithms of Turbo codes are anatomized clearly for a discrete memoryless Gaussian channel. With Monte Carlo simulation, performance of two algorithms is compared under the same constraint condition; after analysis it is proposed that they are identical in nature, the only difference is how to deal with scale of extrinsic information for component decoder to use. Finally, a united form is used to describe two algorithms and some research is done for the dependency on extrinsic information in iterative decoding numerically, from the result it is found that SNR and iterative number do not affect the best scale of extrinsic information used in component decoder.

In this paper a new frequency offset estimation method using repeated sequences is introduced where two steps are involved. In the first step the span of the correlation data is small and a larger estimation range can be achieved. After the frequency offset is compensated, a larger correlation data span is chosen and a precise estimation can be got. Large estimation range and precise estimation can be acquired in the new method. Simulations in AWGN channel and Rayleigh channel verify the validity of the new algorithm.

A multimedia streams self-regulating algorithm based on fuzzy immune PID is proposed to attain the goal of on-line self-regulating of multimedia streams and effective resource management. Model of adaptive session is analyzed, and available bandwidth’ future estimation is achieved. The fuzzy nonlinear approximation of immune’ suppresser is fulfilled by fuzzy rules’ self-tuning with self-tuning factor in full domain. Then, in order to improve the traditional PID algorithm fuzzy nonlinear approximation is combined with immune feedback mechanism to adjust PID factors during the course of multimedia transmission. Simulation validates the theoretical results of MFIPID.

Based on the introduction of the QoS conception in CORBA A/V stream specification and the RSVP-based integrated service model，a integrated QoS model is presented. Then the mapping model and the binding strategies between CORBA A/V Stream QoS and IntServ/RSVP are discussed in detail. A prototype system has been developed to verify the feasibility of the model.

In this paper, a new higher order Alternating Direction Implicit Finite-Difference Time-Domain (ADI-FDTD) formulation in particular, a second-order-in-time, fourth-order-in-space AD-FDTD method is presented for the first time. At the same time ,the unconditional stability of the higher order ADI-FDTD formulation is analytically proved. By analysis of the amplification factors, the numerical dispersion relation is derived. In addition, the numerical dispersion errors are investigated. Finally numerical results indicate that the higher order ADI-FDTD has s better accuracy compared to the ADI-FDTD method.

According to the Kirchhoff approximation for the rough surface scattering and by calculating the shadowing function and characteristic function of the fractal rough sea surface, the formula of the scattering cross section for the conducting fractal sea surface is derived with consideration of the shadowing effect. The influence of the shadowing effect for different RMS slope of the surface is investigated. The distribution of the scattering cross-section for the Gaussian rough surface and fractal rough sea surface is compared with millimeter wave incidence. The angular distribution of the bistatic scattering cross-section from fractal sea surface for different fractal dimension and different spatial frequency is analyzed. The influence of different incident angle, different fractal dimension and shadowing effect on the Doppler spectra of the echo from the fractal sea surface is discussed in detail.

Alternating Direction Implicit-Finite Difference Time Domain(ADI-FDTD) is unconditionally stable and the maximum time step size is not limited by the Courant stability condition, but rather by numerical error. Compared with the conventional FDTD method, the time step size of ADI-FDTD can be enlarged arbitrarily. In this paper 2D PML implementation is proposed for ADI-FDTD in dispersive media using recursive convolution method. ADI-FDTD formulations for dispersive media can be derived from the simplified Perfectly Matched Layer (PML). Numerical results of ADI-FDTD with PML for dispersive media are compared with FDTD. Good agreement is observed.

More and more researches show that network traffic is not Markovian process, but shows the burst nature called “self-similarity” at any time scale .The mathematic models describing network traffic mainly include self-similar process and long range dependence structure. Due to some network parameters obeying heavy tail distribution, network traffic shows the burst nature at large time scale. This paper analyses the drawbacks of the classical network traffic models and performance evaluation, and describes the basic trademarks of evolutionary traffic models. This paper studies three important models of self-similar network traffic: ON/OFF model, user access probability model and fluid flow close loop model, and discusses relative research directions. Some issues and principles that shall be noticed during studying and modeling network traffic are given in the end.