一种燃油流量测量系统设计

燃油流量是飞机燃油系统中的一项重要指标,宽范围、快响应、高精度的燃油流量测量对飞机的性能有着重要的影响。基于机电综合管理系统平台,以DSP+FPGA芯片为核心,根据技术要求设计一种燃油流量测量系统,实现了高精度的频率采集。

Architecture design of GPS software receiver and implementation of its acquisition algorithm with fine frequency estimation

The design of a global positioning system （GPS） software receiver is introduced. This design uses the concept of software radio, and it consists of the following parts： front-end, acquisition, tracking, synchronization, navigation solution and some assisting modules. In the acquisition module, the acquisition algorithm based on circular correlation is utilized. The input data and the local code are converted into the frequency domain by means of the fast Fourier transform （FFT）. After performing circular correlation, the initial phase of the C/A code can be obtained and the cartier frequency can be found in 1 kHz frequency resolution, which is too coarse to use for the tracking loop. In order to improve the frequency resolution, the fine frequency estimation through a phase relationship is then achieved, by which, the frequency resolution is improved dramatically. Experiments show that the inaccuracy of the carrier frequency can be estimated within a few hertz by the fine frequency estimation method, and the fine frequency attained can be directly used for the tracking loop.

Phase Difference Method for DOA Estimation

The phase difference method (PDM) is presented for the direction of arrival (DOA) estimation of the narrowband source. It estimates the DOA by measuring the reciprocal of the phase range of the sensor output spectra at the interest frequency bin. The peak width and variance of the PDM are presented. The PDM can distinguish closely spaced sources with different and unknown center frequencies as long as they are separated with at least one frequency bin. The simulation results show that the PDM has a better resolution than that of the conventional beamforming.

Fast method for spreading sequence estimation of DSSS signal based on maximum likelihood function

To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).

The optimal time-frequency atom search based on a modified ant colony algorithm

this paper, a new optimal time-frequency atom search method based on a modified ant colony algorithm is proposed to improve the precision of the traditional methods. First, the discretization formula of finite length time-frequency atom is inferred at length. Second; a modified ant colony algorithm in continuous space is proposed. Finally, the optimal time- frequency atom search algorithm based on the modified ant colony algorithm is described in detail and the simulation experiment is carried on. The result indicates that the developed algorithm is valid and stable, and the precision of the method is higher than that of the traditional method.

DNN-Based Speech Enhancement Using Soft Audible Noise Masking for Wind Noise Reduction

This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.

Application of frequency estimation algorithm based on a single vector sensor in underwater acoustic communication

A method of high resolution frequency estimation based on a single vector sensor using ESPRIT （Estimating Signal Parameters via Rotational Invariance Techniques） algorithm is proposed and applied to the underwater acoustic （UWA） communication system of frequency modulation. Higher resolution frequency estimation can be obtained by this algorithm using fewer snapshots comparing with the sound intensity frequency estimation. Results of simulation and lake experiment show that the proposed algorithm can improve the communication data rate and reduce the bandwidth of the system. Because higher signal-to-noise ratio （SNR） is demanded, range UWA communication at oresent. this algorithm can be used in high speed short

A NOVEL WIDEBAND ANTENNA DESIGN USING U-SLOT

U-slot patch antennas with П-shaped feed slot are studied, and numerical results based on the FDTD method are presented. The effects of varying physical parameters are investigated with a goal of understanding the coupling among different resonators. It is found that the U-slot patch antenna can be designed to attain 50% impedance bandwidth as well as 30-40% gain bandwidth. By altering the sizes of U-slot and feed slot, the wideband characteristic can be changed into a duai-frequency char- acteristic.

Robust Joint Timing and Frequency Synchronization Algorithm for IEEE802.16e OFDM System

Based on the structures of the short preamble and long preamble, which are defined for synchronization in IEEES02.16e specification, the robust synchronization algorithm for IEEES02.16e OFDM system is proposed. The correlations among the sample sequences in the preamble are investigated, especially the correlation between the first sample sequence and the last sample sequence in the long preamble. The conventional joint timing and frequency synchronization algorithm is reviewed based on the short preamble referring to the algorithm proposed by Schmidl, then a robust joint timing and frequency synchronization algorithm is proposed based on the long preamble. The simulations in the multi-path and frequency selective fading channel show that the proposed algorithm has improved the performances of timing metric plateau, timing offset and synchronization acquisition time even when signal-to-noise ratio is less than -5 dB.

Lightweight design of 45000r/min spindle using full factorial design and extreme vertices design methods

Factors for determining the spindle size are the shaft diameter, positions of bearing and motor, and entire length of the spindle. Then, it is important to find the assembling of the optimal design variables, which satisfy the stiffimss and rotational speed required to the spindle. A general full factorial design method was used to verify some factors that affect the natural frequency of a spindle. It is verified that the shorter shaft length and bearing span length represent the higher natural frequency, and there are some effects according to the change in the levels of factors. The detailed spindle dimension is determined by applying an EVD method, which can define the optimal bearing position through considering the limiting condition. Based on the estimated regression model, the optimal spindle size and bearing distance that can improve the primary natural frequency are obtained, and the influence of design factors on the natural frequency is also analyzed.

Semi-Blind Pilot-Aided Channel Estimation in Uplink Cloud Radio Access Networks

In this paper, a quasi-Newton method fbr semi-blind estimation is derived for channel estimation in uplink cloud radio access networks （C-RANs）. Different from traditional pilot-aided estimation, semiblind estimation utilizes the unknown data symbols in addition to the known pilot symbols to estimate the channel. An initial channel state information （CSI） obtained by least-squared （LS） estimation is needed in semi-blind estimation. BFGS （Brayben, Fletcher, Goldfarb and Shanno） algorithm, which employs data as well as pilot symbols, estimates the CSI though solving the problem provided by maximum-likelihood （ML） principle. In addition, mean-square-error （MSE） used to evaluate the estimation performance can be further minimized with an optimal pilot design. Simulation results show that the semi-blind estimation achieves a significant improvement in terms of MSE performance over the conventional LS estimation by utilizing data symbols instead of increasing the number of pilot symbols, which demonstrates the estimation accuracy and spectral efficiency are both improved by semiblind estimation for C-RANs.

Performance of a novel carrier frequency offset estimation algorithm for OFDM-based WLANs

This paper presents a novel carrier frequency offset estimation (CFO) algorithm for orthogonal frequency division multiplexing (OFDM)-based Wireless Local Area Networks (WLANs). Compared with previous approaches, this paper extends the whole frequency offset acquisition range by embedding a synthetic algorithm according to the preamble structure of WLANs symbols. The numerical results presented support the effectiveness of this algorithm by which the estimation error of the whole carrier frequency offset in the WLANs is effectively decreased.

Non-dominated sorting quantum particle swarm optimization and its application in cognitive radio spectrum allocation

In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.

Study on the Calibration Function of Local Earthquake Magnitude in the Gansu Region

To calculate the deviations between single station magnitudes and average ones by the magnitude residual statistical method,the paper selects 13086 seismic events recorded by the Gansu broadband digital seismic network from January 2009 to December 2012. The frequency distribution and quantitative statistics of the deviations of earthquake magnitude are analyzed. The MLcalibration function is modified and a uniform local magnitude system characteristic of the Gansu region,is obtained.

ADAPTIVE BLIND ESTIMATION ALGORITHM FOR OFDM-MIMO RADIO SYSTEMS OVER MULTIPATH CHANNELS

This paper investigates the blind algorithm for channel estimation of Orthogonal Frequency Division Multiplexing-Multiple Input Multiple Output (OFDM-MIMO) wireless communication system using the subspace decomposition of the channel received complex baseband signals and proposes a new two-stage blind algorithm. Exploited the second-order cyclostationarity inherent in OFDM with cyclic prefix and the characteristics of the phased antenna, the practical HIPERLAN/2 standard based OFDM-MIMO simulator is established with the sufficient consideration of statistical correlations between the multiple antenna channels under wireless wideband multipath fading environment, and a new two-stage blind algorithm is formulated using rank reduced subspace channel matrix approximation and adaptive Constant Modulus (CM)criterion. Simulation results confirm the theoretical analysis and illustrate that the proposed algorithm is capable of tracking matrix channel variations with fast convergence rate and improving acceptable overall system performance over various common wireless and mobile communication links.

Frequency Domain TOA Estimation Algorithm Based on Cross-HOC

High-Order Cumulants （HOC） and cross-correlation was combined to suppress the Gaussian color noises and the tin-related noises in real applications. The cross-HOC TOA estimation model was developed based on the diagonal slice of the forth-cross-cumu-lant. The eigen analysis was carried out, and the eigea noise space and the eigen signal space was achieved. Then the Frequency Domain TOA estimation algorithm based on Cross-HOC was developed. Different simulation experiments were carried out to draw out the conclusions.

BLIND CHANNEL ESTIMATION IN DELAY DIVERSITY FOR FREQUENCY SELECTIVE CHANNELS

Delay diversity is an effective transmit diversity technique to combat adverse effects of fading. Thus far, previous work in delay diversity assumed that perfect estimates of current channel fading conditions are available at the receiver and training symbols are required to estimate the channel from the transmitter to the receiver. However, increasing the number of the antennas increases the required training interval and reduces the available time with in whichdata may be transmitted. Learning the channel coefficients becomes increasingly difficult for the frequency selective channels. In this paper, with the subspace method and the delay character of delay diversity, a channel estimation method is proposed, which does not use training symbols. It addresses the transmit diversity for a frequency selective channel from a single carrier perspective in the form of a simple equivalent flat fading model. Monte Carlo simulations give the performance of channel estimation and the performance comparison of our channel-estimation-based detector with decision feedback equalization, which uses the perfect channel information.

Research on underwater acoustic channel estimation and temperature factors based on FBMC

The complexity of underwater environment poses a challenge to underwater acoustic communication.In marine environment,different temperatures,depths and salinities would affect the performance of acoustic communication.The analysis of the underwater acoustic channel under the influence of temperature factors provides a reference for further study of the underwater acoustic channel estimation problem based on filter bank multi-carrier(FBMC).The FBMC based offset quadrature amplitude modulation(OQAM)technology(FBMC/OQAM)was introduced into the underwater acoustic communication.Based on FBMC,the underwater acoustic channel estimation technology was studied.By changing the pilot structure to adapt to the complex and variable underwater acoustic channel,the iterative method was used to obtain the channel information with higher accuracy and further improve the performance of channel estimation.Theoretical analysis and simulation results show that iterative channel estimation algorithm based on the new interference approximation method(IAM)pilot proposed in this paper has better performance in underwater acoustic channel.

Adaptive bands filter bank optimized by genetic algorithm for robust speech recognition system

Perceptual auditory filter banks such as Bark-scale filter bank are widely used as front-end processing in speech recognition systems.However,the problem of the design of optimized filter banks that provide higher accuracy in recognition tasks is still open.Owing to spectral analysis in feature extraction,an adaptive bands filter bank (ABFB) is presented.The design adopts flexible bandwidths and center frequencies for the frequency responses of the filters and utilizes genetic algorithm (GA) to optimize the design parameters.The optimization process is realized by combining the front-end filter bank with the back-end recognition network in the performance evaluation loop.The deployment of ABFB together with zero-crossing peak amplitude (ZCPA) feature as a front process for radial basis function (RBF) system shows significant improvement in robustness compared with the Bark-scale filter bank.In ABFB,several sub-bands are still more concentrated toward lower frequency but their exact locations are determined by the performance rather than the perceptual criteria.For the ease of optimization,only symmetrical bands are considered here,which still provide satisfactory results.

Multiple Reader Algorithm for Sports Timing Systems and Its Application at Low Frequency Bandwidth

In sports timing systems,P2P communication is used at low frequency bandwidths(under 135 KHz) between tags and readers in the RFID field.However,in such cases,collisions tend to occur when a reader deals with multiple RFID tags simultaneously.To overcome this issue,a sports timing system including a Multi Reader Controller(MRC)loaded with an advanced multiple reader algorithm and application was created and applied at large-scale citizens' marathon events.In these cases,a large number of people pass over the installed urethane type's antenna mat continually during a short period of time.This study verified the superiority of the improved algorithm and application through the on-thespot application of the multi reader algorithm and application program,which allows us to smoothly measure runners' times through multiaccess reading for rapid collision avoidance.