Detection of UAV Target Based on Continuous Radon Transform and Matched Filtering Process for Passive Bistatic Radar

Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.

Ion beam figuring of continuous phase plates based on the frequency filtering process

Ion beam figuring （IBF） technology is an effective technique for fabricating continuous phase plates （CPPs） with small feature structures. This study proposes a multi-pass IBF approach with different beam diameters based on the frequency filtering method to improve the machining accuracy and efficiency of CPPs during IBF. We present the selection principle of the frequency filtering method, which incorporates different removal functions that maximize material removal over the topographical frequencies being imprinted. Large removal functions are used early in the fabrication to figure the surface profile with low frequency. Small removal functions are used to perform final topographical correction with higher fre- quency and larger surface gradient. A high-precision surface can be obtained as long as the filtering frequency is suitably selected. This method maximizes the high removal efficiency of the large removal function and the high corrective capability of the small removal function. Consequently, the fast convergence of the machining accuracy and efficiency can be achieved.

Filtering Two-Phase Medium in Pipes and Channels on the Entrance Part of Flow

Processes of filtering two-phase media in filtration devices play an important role in various industries. Significant role in the process of filtering is the initial section of flow, which defines the basic parameters： the profile and value of the velocity, pressure gradients, concentration and dispersion of sediment particles, etc. The problem is solved by the method of surfaces of equal cost, the results enabled to establish the influence of the input section on the filtering process.

Improved preprocessed Yaroslavsky filter based on shearlet features

An improved preprocessed Yaroslavsky filter（IPYF）is proposed to avoid the nick effects and obtain a better denoising result when the noise variance is unknown.Different from its predecessors,the similarity between two pixels is calculated by shearlet features.The feature vector consists of initial denoised results by the non-subsampled shearlet transform hard thresholding（NSST-HT）and NSST coefficients,which can help allocate the averaging weights more reasonably.With the correct estimated noise variance,the NSST-HT can provide good denoised results as the initial estimation and high-frequency coefficients contribute large weights to preserve textures.In case of the incorrect estimated noise variance,the low-frequency coefficients will mitigate the nick effect in cartoon regions greatly,making the IPYF more robust than the original PYF.Detailed experimental results show that the IPYF is a very competitive method based on a comprehensive consideration involving peak signal to noise ratio（PSNR）,computing time,visual quality and method noise.

Design of a downlink algorithm for rotary steering(logging while drilling)systems

For logging while drilling(LWD)systems,it is necessary to adjust the working state of the downhole tools in real-time according to different operating conditions.In this paper,on the basis of the characteristics of LWD systems,a mud pressure-apperceived downlink system was examined.For the design of this system,a signal acquisition and processing board was created based on a piezoelectric ceramic sensor to acquire the mud pressure signal.The error sources of the downlink command sending process were analyzed,and an error accumulation compensation processing algorithm was proposed to improve the recognition success rate of the downhole system.Moreover,to reduce noise interference on the characteristics of the mud impulse signal,a fi ltering algorithm was proposed based on the empirical mode decomposition method,and the success rate of instruction issuance was determined by identifying feedback instructions.Field tests were conducted to further improve the system,the results of which suggested that the system had good mud adaptability,high recognition success rate,and a certain application value.

Research on fault detection method for heat pump air conditioning system under cold weather

Building energy consumption accounts for nearly 40% of global energy consumption, HVAC （Heating, Ventilating, and Air Conditioning） systems are the major building energy consumers, and as one type of HVAC systems, the heat pump air conditioning system, which is more energy-efficient compared to the traditional air conditioning system, is being more widely used to save energy. However, in northern China, extreme climatic conditions increase the cooling and heating load of the heat pump air conditioning system and accelerate the aging of the equipment, and the sensor may detect drifted parameters owing to climate change. This non-linear drifted parameter increases the false alarm rate of the fault detection and the need for unnecessary troubleshooting. In order to overcome the impact of the device aging and the drifted parameter, a Kalman filter and SPC （statistical process control） fault detection method are introduced in this paper. In this method, the model parameter and its standard variance can he estimated by Kalman filter based on the gray model and the real-time data of the air conditioning system. Further, by using SPC to construct the dynamic control limits, false alarm rate is reduced. And this paper mainly focuses on the cold machine failure in the component failure and its soft fault detection. This approach has been tested on a simulation model of the ＂Sino-German Energy Conservation Demonstration Center＂ building heat pump air-conditioning system in Shenyang, China, and the results show that the Kalman filter and SPC fault detection method is simple and highly efficient with a low false alarm rate, and it can deal with the difficulties caused by the extreme environment and the non-linear influence of the parameters, and what＇s more, it provides a good foundation for dynamic fault diagnosis and fault prediction analysis.

A gray-natural logarithm ratio bilateral filtering method for image processing

A new method based on gray-natural logarithm ratio bilateral filtering is presented for image smoothing in this work. A new gray-natural logarithm ratio range filter kernel, leading to adaptive magnitude from image gray distinction information, is pointed out for the bilateral filtering. The new method can not only well restrain noise but also keep much more weak edges and details of an image, and preserve the original color transition of color images. Experimental results show the effectiveness for image denoising with our method.

Mathematical Modeling of Non-Isothermal Flow of Thin Layer of Two-Phase Medium Permeable Surface

Processes of filtering two-phase media in filtration devices play an important role in various industries. Significant role in the process of filtering is the initial section of flow, which defines the basic parameters： the profile and value of the velocity, pressure gradients, concentration and dispersion of sediment particles, etc.. The problem is solved by the method of surfaces of equal cost, the results enabled to establish the influence of the input section on the filtering process.

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.

Flexible polarization demultiplexing method based on an adaptive process noise covariance Kalman filter

A flexible polarization demultiplexing method based on an adaptive Kalman filter（AKF） is proposed in which the process noise covariance has been estimated adaptively. The proposed method may significantly improve the adaptive capability of an extended Kalman filter（EKF） by adaptively estimating the unknown process noise covariance. Compared to the conventional EKF, the proposed method can avoid the tedious and time consuming parameter-by-parameter tuning operations. The effectiveness of this method is confirmed experimentally in 128 Gb/s 16 QAM polarization-division-multiplexing（PDM） coherent optical transmission systems. The results illustrate that our proposed AKF has a better tracking accuracy and a faster convergence（about 4 times quicker）compared to a conventional algorithm with optimal process noise covariance.

On Markov Chains Induced by Partitioned Transition Probability Matrices

Let S be a denumerable state space and let P be a transition probability matrix on S. If a denumerable set M of nonnegative matrices is such that the sum of the matrices is equal to P, then we call M a partition of P. Let K denote the set of probability vectors on S. With every partition M of P we can associate a transition probability function PM on K defined in such a way that if p ∈ K and M ∈M are such that ｜｜pM｜｜ 〉 0, then, with probability ｜｜pM｜｜ the vector p is transferred to the vector pM/｜｜pM｜｜. Here ｜｜·｜｜ denotes the/1-norm. In this paper we investigate the convergence in distribution for Markov chains generated by transition probability functions induced by partitions of transition probability matrices. The main motivation for this investigation is the application of the convergence results obtained to filtering processes of partially observed Markov chains with denumerable state space.

Novel distributed passive vehicle tracking technology using phase sensitive optical time domain reflectometer

A novel distributed passive vehicle tracking technology is proposed and demonstrated. This technology is based on a phase-sensitive optical time domain reflectometer（Φ-OTDR） that can sense and locate vibrations. Two algorithms, dynamic frequency-space image and 2D digital sliding filtering, are proposed to distinguish a car＇s moving signals from severe environmental noises and disturbances. This technology is proved effective by field experiments for tracking a single car and multiple cars. This work provides a new distributed passive way for real-time vehicle tracking and this technology will be extremely important for traffic controlling and public safety in modern society.

Bioavailability of wastewater derived dissolved organic nitrogen to green microalgae Selenastrum capricornutum,Chlamydomonas reinhardtii,and Chlorella vulgaris with/without presence of bacteria

Effluent dissolved organic nitrogen（DON） is problematic in nutrient sensitive surface waters and needs to be reduced to meet demanding total dissolved nitrogen discharge limits.Bioavailable DON（ABDON） is a portion of DON utilized by algae or algae ＋ bacteria,while biodegradable DON（BDON） is a portion of DON decomposable by bacteria.ABDON and BDON in a two-stage trickling filter（TF） wastewater treatment plant was evaluated using three different microalgal species,Selenastrum capricornutum,Chlamydomonas reinhardtii and Chlorella vulgaris and mixed cultured bacteria.Results showed that up to80% of DON was bioavailable to algae or algae ＋ bacteria inoculum while up to 60% of DON was biodegradable in all the samples.Results showed that C.reinhardtii and C.vulgaris can be used as a test species the same as S.capricornutum since there were no significant differences among these three algae species based on their ability to remove nitrogen species.

A New Approach to State Estimation for Uncertain Linear Systems in a Moving Horizon Estimation Setting

This paper addresses the state estimation problem for linear systems with additive uncertainties in both the state and output equations using a moving horizon approach. Based on the full information estimation setting and the game-theoretic approach to the H∞filtering, a new optimization-based estimation scheme for uncertain linear systems is proposed, namely the H∞-full information estimator, H∞-FIE in short. In this formulation, the set of processed data grows with time as more measurements are received preventing recursive formulations as in Kalman filtering. To overcome the latter problem, a moving horizon approximation to the H∞-FIE is also presented, the H∞-MHE in short. This moving horizon approximation is achieved since the arrival cost is suitably defined for the proposed scheme. Sufficient conditions for the stability of the H∞-MHE are derived. Simulation results show the benefits of the proposed scheme when compared with two H∞filters and the well-known Kalman filter.