Study of Acquisition in a Rake Receiver Based on Digital Matched-filter

The Rake receiver based on digital matched filter(DMF) is studied extensively in order to investigate the performance of the PN code acquisition.By using the state transition diagram,the authors derive the analytic expressions of the mean acquisition time of the Rake receiver based on DMF over frequency-selective channel.Numerical analysis is also given.It is shown that the proposed Rake receiver based on DMF can accelerate the process of PN code acquisition.Because there are many resolved multipath components over frequency-selective channel,the detection probability of Rake receiver is larger than the conventional receiver.If more fingers of Rake receiver are available,then the mean acquisition time is longer and the threshold of detector can be set more widely.     

A Data Detector Based on Channel Equalizer Designed for the Downlink of CDMA Systems

In code-division multiple-access (CDMA) systems,sub-optimum multi-user or joint detection algorithms have been studied recently, which are mostly designed for the uplink situation. The algorithms are too complex to implement for the downlink situation. The conventional receiver consisting of matched filters is often inefficient in eliminating MAI. The authors propose a data detection algorithm designed for downlink of CDMA systems which introduce channel equalization to eliminate MAI. It consists of a channel equalizer and code matched filter. The equalization algorithm is based on zero forcing (ZF) criterion.The performance of the algorithm is better than metched filter's and its complexity is cower than tunt of sub-optimum multi-user detection.     

Multi-target tracking algorithm based on adaptive sampling interval in wireless sensor networks

Multi-target tracking is a hot topic of current research on wireless sensor networks (WSN). Based on adaptive sampling interval, we propose a multi-target tracking algorithm in order to save energy consumption and prevent tracking lost for WSN. We contrast the targets moving model by using the position metadata, and predicte the targets moving status based on extended Kalman filter (EKF).we adopt the probability density function (PDF) of the estimated targets to establish the tracking cluster. By defining the tracking center, we use Markov distance to quantify the election process of the main node (MN). We comput targets impact strength through the targets importance and the distance to MN node, and then use it to build tracking algorithm. We do the simulation experiment based on MATLAB, and the experiment results show that the proposed algorithm can accurate predict the trajectory of the targets, and adjust the sampling interval while the targets were moving. By analyzing the experiments data, we know that the proposed algorithm can improve the tracking precision and save the energy consumption of WSN obviously.     

The application research on improvement of constant sinusoidal signal sampling precision based on adaptive filter

A novel scheme is present to improve the conversion accuracy of ADC. The proposed approach uses adaptive sinusoidal filter. For the measurement of the signal with given frequency, the automatic adjustment of filter coefficients is based on least mean-square error rule, which is a mathematical tool can be employed to make filter output signal achieve the best approximation to the needed one. Then based on the result, it is able to get the amplitude and phase of the measured signal accurately. MATLAB software is used to verify the effectiveness of the algorithm. It proves that adaptive filter has improved the accuracy and signal-to-noise ratio of ADC, which is equal to increase the conversion digits.     

汽车转弯自动照明控制系统数据采集滤波方法

为了减少汽车转弯自动照明控制系统数据滤波处理中的延时,在滑动中值滤波方法基础上,提出了一种带补偿的限幅滑动中值滤波算法,通过补偿的方式跟随信号的变化趋势。该算法通过2个步骤完成滤波,先对数据进行带补偿方式的限幅处理,再进行滑动中值滤波处理。该算法综合了滑动中值滤波法的实时性以及限幅滤波法对偶然性干扰滤除的有效性,实现更准确的滤波。仿真与实测结果表明,与滑动中值滤波方法相比较,改进后的算法滤波能够实时地滤除数据中的干扰,处理时间可减少62%,滤波效果较好,且速度信号的数据滞后时间较短,实时性较高,满足系统设计要求。     

Multipath interference cancellation RAKE receiver with nested structure

A multipath interference cancellation RAKE receiver with nested structure is proposed based on successive interference cancellation method. In the proposed method, the present branch and the demodulated branch form a substructure of the RAKE receiver, while the RAKE substructures are nested. The data estimate of the present branch is obtained by the maximum ratio combination of the demodulator output in the corresponding RAKE substructure. The update of the regeneration signal is achieved by replacing the previous branch data with the present branch data estimate . Performance of the new RAKE receiver was analyzed. Theoretical analysis and simulation results show that the new RAKE receiver with simple structure and easy implementations can suppress the multipath interference and improves the BER performance.     

Improved DMT systems with multiple time domain equalization

DFT(discrete fourier transform)based discrete multi tone (DMT) transceivers have achieved great success in high speed data transmission. When the cyclic prefix is no shorter than the channel impulse response (CIR), the DMT system is ISI (inter symbol interference) free. For the channels with very long CIR, such as DSL loops, time domain equalizer (TEQ) is typically added at the receiver to shorten the impulse response and improve performance. This paper proposes a filter banks approach to design the TEQ to maximize the bit rate. A DMT system is introduced with a pair of complex conjugating TEQs. For the design and implementation costs, the scheme shows the best performance price ratio.     

The Extended Kalman Filter Data Fusion Algorithm Based on Discrete Stationary Wavelet Transformation

It is difficult to establish precise mathematical model in extended Kalman filter data fusion algorithm for GPS/ DR integrated vehicle navigation system, an improved extended Kalman filter data fusion algorithm is put forward based on Discrete stationary wavelet transformation. The simulation results show that the algorithm is better than the extended Kalman filter data fusion algorithm, and is available for GPS/DR integrated vehicle navigation system.     

A time-varying signal processing method for Coriolis mass flowmeter

The mass flowrate of Coriolis mass flowmeter in practical application has slow changes with time. To solve the problem, an improved time-varying signal model whose frequency, amplitude and phase are time-varying based on the random walk model is established firstly. A new algorithm of adaptive notch filter with the capability of tracking frequency variation is applied to filter the sensor output signal of Coriolis mass flowmeter and its frequency is calculated next. An adaptive line enhancer based on the mentioned notch filter extracts fundamental frequency signal from noisy data. Then, by short window intercepting, the revised sliding DTFT recursive algorithm is introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and phase difference obtained, the time interval between the two signals is calculated and then the mass flowrate is derived. The simulations and field test results show that the proposed method can not only track the change of frequency and phase, but also ensure the calculation accuracy when measuring small phase difference. The computational load of the algorithm is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.     

Frequency tracking method and simulation for coriolismass flowmter based on a new adaptive notch filter

In order to improve the long-playing frequency tracking ability in the signal processing for coriolis mass flowmeter (CMF) , a new IIR adaptive notch filter (ANF) is developed via steiglitz-mcBride method (SMM) and applied to filter the sensor output signal whose frequency, amplitude and phase are time-varying following the random walk model. The proposed method can detect the signal frequency fleetly and track the frequency variations continuously. The tracking performances of the proposed method and the adaptive lattice notch filter (LANF) method are investigated with computer simulations. Simulations demonstrate the superiority of the proposed method and show it has advantages of fast convergence rate, insensitivity to initial phase variations, and higher long-playing tracking stability and accuracy than LANF method.     

Influence of MUD on the System Capability of CDMA

In CDMA communication system, the relativities between users result in Multiple Access Interference (MAI). With the increase of users, MAI becomes the main jam of broadband CDMA communication system. Multi-User Detection (MUD) is the most important technology of anti-jamming in the broadband CDMA communication system, which can eliminates MAI effectively by using the information of all user signals to detection single. This paper analyze the expression of system capability without MUD and with MUD, and puts forward the way to increase system capability by using MUD. Then the influence of MUD on CDMA system capability is discussed by MATLAB emulation. Basing analysis and emulation, the conclusion is got: the higher the MUD efficiency, the better the improvement of CDMA system capability; under the same MUD efficiency, the lower data rate, the smaller inter-cell interference, the lower the ratio of bit energy to power spectrum, the better the improvement of CDMA system capability.     

Improved Sage-Husa algorithm and its application in industrial online measurement

An improved Sage-Husa adaptive filter algorithm is proposed based on the existing methodologies in light of the complex and changing environment of the industrial online measurement. This algorithm,after a new observed value is obtained,first judges whether the filter is in a normal state by the filtering divergence criterion,if not,it judges whether the new observed value is an outlier and takes countermeasures varying with the judgment so as to improve the performance of the Sage-Husa algorithm in industrial measurement. The result indicates that compared with traditional methodologies,this new algorithm is applicable to measure the location of the center point of laser beam in a simulated industrial environment,makes accurate judgment about the system status,features better precision,practicality and robustness and thus can satisfy the requirements of industrial online measurement.     

Signal Processing Method for Coriolis Mass Flowmeter Based on Lattice Notch Filter and DTFT

A novel signal processing method for Coriolis mass flowmeter is proposed based on time-varying signal model. First, an adaptive lattice notch filter is applied to filter the output signal, whose frequency, amplitude and phase are time-varying based on the random walk model, of Coriolis mass flowmeter to get its frequency and enhanced signal. Then, by short window intercepting, the DTFT algorithm with negative frequency contribution is introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference, the time interval between two signals is calculated. Simulation results show that the proposed method is efficient. Furthermore, the computation of algorithms is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.     

State of charge estimation of lithium iron phosphate batteriesbased on adaptive Kalman filters

The Kalman filter algorithm can be used to estimate the state of charge (SOC) of power batteries, however, it easily causes divergence due to uncertain of system noise and its estimation performance is affected by model. An adaptive Kalman filter algorithm is adopted to dynamically estimate SOC of lithium iron phosphate batteries for application in electric vehicles. At first, an equivalent circuit model, appropriate for SOC estimation is built after studying battery models. Then some charging and discharging experiments are carried out for parameter identification and the results are verified. At last, the adaptive Kalman filter algorithm is used on this model for on-line SOC estimation under unknown interfering noise. Simulation results show that adaptive Kalman filter method can correct SOC estimation error caused by tiny model error online, and the estimate accuracy is higher than Kalman filter method. Adaptive Kalman filter algorithm can also correct the initial error. Full-cycle test in electric vehicles proves that the algorithm is appropriate for SOC estimation of lithium iron phosphate battery.     

基于改进SVM分类器的动作识别方法

利用智能手机加速度传感器信号,提出一种改进的动作识别方法以降低传统动作识别方法的复杂程度,提高识别率。在特征提取时用盲选法,即用PCA(principal component analysis)进行特征值的降维和去除多维间的干扰,而所选特征没有对应的物理意义;并在分类识别中将遗传算法应用到SVM(support vector machine)分类器参数优化中。通过实验表明,该方法能够对日常的走路、站立、跑及上下楼等动作进行准确的识别。     

The Application of Narrowband Interference Suppression in Direct Sequence Spread Spectrum

In order to improve the system effect, it is necessary take the technique of digital signal process to suppress interference, because of the finite gain and the narrow-band interference in system of direct sequence spread spectrum. The authors design a new filter structure improving on tunable digital heterodyne adaptive notch filters. This filter can adaptively track the interference frequency and control the bandwidth and depth of notch, which has the excellent agility and utility. The experiment proves this method overcomes limitation of other interference suppressions, hardly weaken the system performances, enhances the stability of the filter system, and can quickly track the interference frequency.     

Adaptive relay selection algorithm in decode-and-forward cooperative communication networks

An adaptive relay selection algorithm(ARS) is proposed to optimize the performance of decode-and-forward cooperative communication networks, both system outage probability and average numbers of cooperative relays are analyzed. When the direct transmission between source and destination is fail, according to the channel quality, the destination orders relay nodes in the decode set, and the ordered relays are included in cooperation in turn until the instantaneous received SNR at destination is not smaller than the preset SNR threshold. Simulation results show that, the proposed algorithm can get optimal outage performance, decrease the average numbers of cooperative relays efficiently, to incrense bandwidth efficiency and reduce system overhead.     

Image denoising based on the complex direction of filter banks and blockshrink

A new image denoising algorithm based on the complex direction of filter bands and BlockShrink is proposed. The image is decomposed based on the complex direction of filter bands to obtain the coefficients. Then, according to the coefficient correlation, the block threshold method is used to select the best block size and the threshold. In this way, the unbiased risk estimation of each sub-band is minimized. The algorithm is entirely data-driven easy to implement and with good visual effects. Experiments show that the proposed algorithm increase the PSNR by 0.6 percent compared with the algorithm based on DWT-BlockShrink transform, and the edge and countour information are more clearly.     

Image denoising based on adaptive graph regularization

Adaptive regularization can select different parameters based on the features of local areas in an image, which can differentiate the edges and noise in an image flexibly. An adaptive graph regularization is proposed based on graph spectral theory and adaptive regularization, which uses the Non local means to generate the weighting function of graph. The adaptive graph regularization equation is used to filter the noisy image. Simulation results show that the proposed method can effectively remove the noise and is superior to other graph theory based partial differential equation methods.     

An optimal equivalent subchannel algorithm for low voltage power line communication system

According to the low voltage power line channel features,combined with adaptive bit loading and power allocation algorithm,an optimal equivalent subchannel algorithm is proposed.Under the condition of fixed amount of transmitted bits and the minimum transmitted power model,impact of optimal equivalent subchannel on the system performance is studied.The optimization algorithm sorts subchannels with similar transmission features into groups,thus the signaling load can be reduced,and the spectrum can be better used.The simulation results show that system can get lower bit error rate(BER) by adopting optimal equivalent subchannel algorithm.