Noise level estimation method with application to EMD-based signal denoising

This paper proposes a new signal noise level estimation approach by local regions. The estimated noise variance is applied as the threshold for an improved empirical mode decomposition（EMD） based signal denoising method. The proposed estimation method can effectively extract the candidate regions for the noise level estimation by measuring the correlation coefficient between noisy signal and a Gaussian filtered signal. For the improved EMD based method, the situation of decomposed intrinsic mode function（IMFs） which contains noise and signal simultaneously are taken into account. Experimental results from two simulated signals and an X-ray pulsar signal demonstrate that the proposed method can achieve better performance than the conventional EMD and wavelet transform（WT） based denoising methods.

Elastic Characteristic Extraction Method of Underwater Target Based on Adaptive Filtering

In this paper, a kind of elastic characteristic extraction method of underwater targets based on adaptive filtering is introduced. The kernel of the method is the recursive least square （RLS） algorithm. Firstly, the geometric scattering signal is fit by using the echo signal and the incident signal. Then, the frequency spectrum of the echo signal and the geometric scattering signal are calculated. At last, the frequency spectrum of the elastic scattering signal is obtained. The research of the simulation and lake experiment is carried on. As the results show, the formants of the elastic signal frequency spectrum can be precisely extracted by the algorithm, and the extraction algorithm can apply to extracting the elastic characteristic from the echo signal in a real underwater acoustics environment.

PREDICTION OF OCEANIC DATA

The Kalman filter is used to predict the velocity of littoral current, the wave direction, the sea depth and the wave steepness. In this paper the Kazumasa model has been modified to deal with two cases: 1) For the positions a bit far from the shore, the interaction between the velocity of littoral current as well as the wave direction and the sea depth as well as the wave steepness must be considered. 2) For the positions very close to the shore, three new parameters describing the asymmetry wave are introduced to deal with wave breaking. The results from the modified model are compared with observed data, and the comparison indicates that the modified model is better and capable of giving more accurate results.

Radio Disturbance Suppression for Ground Wave Radar

A new method of single sample polarization filtering is proposed. The algorithm is fast and suitable for the polarization processing of stationary or nonstationary polarized disturbed signals with one or more independent disturbances. A ground wave polarimetric radar with the ability of radio disturbance suppression is then introduced. Some numerical results demonstrate the effectiveness of single sample polarization filtering method for ground wave polarimetric radar.

Natural Gradient Approach to Multichannel Blind Deconvolution

In this paper we study the geometrical structures of FIR filters and their application to multichannel blind deconvolution. First we introduce a Lie group structure and a Riemannian structure on the manifolds of the FIR filters. Then we derive the natural gradients on the manifolds using the isometry of the Riemannian metric. Using the natural gradient, we present a novel learning algorithm for blind deconvolution based on the minimization of mutual information. Some properties of the learning algorithm, such as equivariance and stability are also studied. Finally, the simulations are given to illustrate the effectiveness and validity of the proposed algorithm.

Stochastic Analysis of Short-Term Structural Responses and Fatigue Damages of A Submerged Tension Leg Platform Wind Turbine in Wind and Waves

In connection with the design of floating wind turbines,stochastic dynamic analysis is a critical task considering nonlinear wind and wave forces.To study the random structural responses of a newly designed submerged tension leg platform(STLP)wind turbine,a set of dynamic simulations and comparison analysis with the MIT/NREL TLP wind turbine are carried out.The signal filter method is used to evaluate the mean and standard deviations of the structural response.Furthermore,the extreme responses are estimated by using the mean upcrossing rate method.The fatigue damages for blade root,tower,and mooring line are also studied according to the simulated time-series.The results and comparison analysis show that the STLP gives small surge and pitch motions and mooring line tensions in operational sea states due to the small water-plane area.Additionally,in severe sea states,the STLP gives lower extreme values of platform pitch,slightly larger surge and heave motions and better towerbase and mooring line fatigue performances than those of the MIT/NREL TLP.It is found that the STLP wind turbine has good performances in structural responses and could be a potential type for exploiting the wind resources located in deep waters.

On measured-error pretreatment of bionic polarization navigation

A signal pre-treatment algorithm based on combination of 3-dimension system identification and Kalman filtering estimation（3DSKE）is proposed.The aim of designing the 3DSKE algorithm is to reduce errors caused by random noise,but leave the systematical errors caused by signal source remained to be solved by a special method.The 3DSKE algorithm is especially suitable for time series of pure measured data without dynamic equation and on-line real-time execution.The simulated result shows that the 3DSKE algorithm can help the basic theoretic calculation to realize feasible,stable,fast,high accurate and auto-executing computing process for the navigation applications.

Application of wavelet scale correlation filtering and its improved algorithm in signal processing with a spark sound source

It is seriously interfered by ship noise when analyzing and extracting broadband spark sound source signal. In the energy concentrated domain which is below 5 kHz, the traditional scale correlation filtering algorithm, which is based on adjacent-scale correlation, has limited anti-interference ability due to the low signal-to-noise ratio （SNR） and similar Lipschitz exponent characteristic of each other. However, because different frequency bands of the broadband electric spark signal have different noise interferences, the filtering algorithm based on adjacent-scale correlation is adapted to high SNR and small-scale high-frequency wavelet coefficients filtering; the filtering algorithm based on cross-scale correlation is adapted to low SNR and large-scale low-frequency wavelet coefficients filtering, and the threshold coefficient selection method had been corrected in the algorithm. It is shown that the filtering algorithm has a good filtering effect and extracts the broadband spark sound source signal effectively; it is applicable to broadband underwater acoustic signM processing in the presence of narrow-band strong interference background noise.

All-optical NRZ-to-AMI conversion using linear filtering effect of silicon microring resonator

We experimentally demonstrate 10-Gb/s format conversion from non-return-to-zero （NRZ） to alternatemark-inversion （AMI） using the linear filtering effect of silicon microring resonator. Our discussion and analysis in simulation further show that a 10-Gb/s AMI signal with good quality can be obtained by a resonator with a notch depth larger than 25 dB when the 3-dB bandwidth is 0.4 nm.

Ultrahigh speed OOK-to-PSK conversion using linear filtering in silicon ring resonators

A scheme to achieve ultrahigh speed all-optical format conversion from on-off keying （OOK） to phase-shift keying （PSK） by using the linear filtering in the silicon ring resonators is proposed. It is shown that the OOK-to-PSK conversion can be achieved through a linear signal processing. Simulation results are provided for the 160-Gb/s non-return-to-zero （NRZ）-to-PSK and carrier-suppressed （CS） return-to-zero （RZ）-to-（CS）RZPSK conversions.

Particle filter based visual tracking with multi-cue adaptive fusion

To improve the robustness of visual tracking in complex environments such as: cluttered backgrounds, partial occlusions, similar distraction and pose variations, a novel tracking method based on adaptive fusion and particle filter is proposed in this paper. In this method, the image color and shape cues are adaptively fused to represent the target observation; fuzzy logic is applied to dynamically adjust each cue weight according to its associated reliability in the past frame; particle filter is adopted to deal with non-linear and non-Gaussian problems in visual tracking. The method is demonstrated to be robust to illumination changes, pose variations, partial occlusions, cluttered backgrounds and camera motion for a test image sequence.

Processing for laser radar range images

Imaging laser radar can give intensity and range images,which provide integrated 3-dimensional (3D) information about objects.However, dropouts and range anomalies exacerbate range images, which makes their background cluttered and target blurred.For background suppression,a new algorithm that combines intensity image and its mean is presented.By using this algorithm to process actual laser radar range images, most background noises are suppressed.According to range anomalies characteristics,multitemplate selection order mean filtering algorithm is presented and used for actual ladar range images where the distance between two targets is 77 m. This algorithm obtains the clear range image in which the interval of two objects is 75 m.The result shows that the processing algorithm is correct and effective.

Robustness estimation of software-synchronized all-optical sampling for fiber communication systems

The robustness of the software-synchronized all-optical sampling for optical performance monitoring is estimated for 10-Gb/s fiber communication systems. It reveals that the software-synchronized algorithm is sensitive to the signal degradation caused by chromatic dispersion and nonlinearity in optical fibers. The influence of timing jitter and amplitude fluctuation of the sampling pulses is also investigated. It is found that stringent requirements are imposed on the quality of the sampling pulse and the tolerance of 1-dB Q penalty is measured. Considering the practically available optical sampling pulse sources, the results indicate that the amplitude fluctuation of the sampling pulses has the dominant impacts on the software-synchronized method.

Morphological self-organizing feature map neural network with applications to automatic target recognition

The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

Track before detect for point targets with particle filter in infrared image sequences

The problem of detecting and tracking point targets in a sequence of infrared images with very low signalto-noise ratio (SNR) is investigated in this paper. A track before detect algorithm for infrared (IR) point target is developed based on particle filter. The particle filter is used to estimate the state of the target in track stage. The unnormalized weights of the output of the filter are used to approximately construct the likelihood ratio for hypothesis test in detection stage. Experiment results with the real image sequences that SNR is about 2.0 show that the proposed algorithm can successfully detect and track point target.

Modified fast Fourier transform in FBMC for satellite communications

In this paper,a Doppler scaling fast Fourier transform（Doppler-FFT）algorithm for filter bank multi-carrier（FBMC）is proposed,which can efficiently eliminate the impact of the Doppler scaling in satellite communications.By introducing a Doppler scaling factor into the butterfly structure of the fast Fourier transform（FFT）algorithm,the proposed algorithm eliminates the differences between the Doppler shifts of the received subcarriers,and maintains the same order of computational complexity compared to that of the traditional FFT.In the process of using the new method,the Doppler scaling should be estimated by calculating the orbital data in advance.Thus,the inter-symbol interference（ISI）and the inter-carrier interference（ICI）can be completely eliminated,and the signal to interference and noise ratio（SINR）will not be affected.Simulation results also show that the proposed algorithm can achieve a 0.4 d B performance gain compared to the frequency domain equalization（FDE）algorithm in satellite communications.