统计分析方法在大气环境监测数据符合性分析中的应用探讨

通过汇总分析气井的试气环境监测数据,选择AERMOD模式,运用EIAProA软件模拟预测试气SO2浓度,对实测和预测数据进行F检验和t检验,验证其方差是否符合显著性要求,同时检验其相关系数、系统均方差和非系统均方差,结果表明符合指数,满足论文预设的70%的要求。

Establishment and tests of EnOI assimilation module for WAVEWATCH Ⅲ

In this paper, we propose a parallel data assimilation module based on ensemble optimal interpolation （EnOI）. We embedded the method into the full-spectral third-generation wind-wave model, WAVEWATCH III Version 3.14, producing a wave data assimilation system. We present our preliminary experiments assimilating altimeter significant wave heights （SWH） using the EnOI-based wave assimilation system. Waters north of 15°S in the Indian Ocean and South China Sea were chosen as the target computational domain, which was two-way nested into the global implementation of the WAVEWATCH III. The wave model was forced by six-hourly ocean surface wind velocities from the cross-calibrated multi-platform wind vector dataset. The assimilation used along-track SWH data from the Jason-2 altimeter. We evaluated the effect of the assimilation on the analyses and hindcasts, and found that our technique was effective. Although there was a considerable mean bias in the control SWHs, a month-long consecutive assimilation reduced the bias by approximately 84% and the root mean-square error （RMSE） by approximately 65%. Improvements in the SWH RMSE for both the analysis and hindcast periods were more significant in July than January, because of the monsoon climate. The improvement in model skill persisted for up to 48 h in July. Furthermore, the SWH data assimilation had the greatest impact in areas and seasons where and when the sea-states were dominated by swells.

Mobile Robot Localization and Navigation System Based on Monocular Vision

A system for mobile robot localization and navigation was presented.With the proposed system,the robot can be located and navigated by a single landmark in a single image.And the navigation mode may be following-track,teaching and playback,or programming.The basic idea is that the system computes the differences between the expected and the recognized position at each time and then controls the robot in a direction to reduce those differences.To minimize the robot sensor equipment,only one omnidirectional camera was used.Experiments in disturbing environments show that the presented algorithm is robust and easy to implement,without camera rectification.The rootmean-square error(RMSE) of localization is 1.4,cm,and the navigation error in teaching and playback is within 10,cm.

Discrete Sliding Mode Control of an Input-output System with Stochastic Disturbance

This paper presents the discrete adaptive sliding mode control of input-output non-minimum phase system in the presence of the stochastic disturbance. The non-minimum phase system can be transformed into a minimum phase system by a operator. According to the minimum phase system, the controller and the adaptive algorithm we designed ensures the stability of system and holds that the mean-square deviation from the sliding surface is minimized.

Complexity-reduced ICI cancellation for OFDM system over doubly-selective channels

In doubly-selective fading wireless channel, the conventional orthogonal frequency division multi-plexing （OFDM） receivers for inter-cartier interference （ICI） compensation require extensive computations. To obtain an effective balance between performance and complexity, the whole channel response matrix was decomposed into a sequence of submatrix, and then a novel equalizer based on minimum mean square error （MMSE） criterion was presented to combat the ICI. Furthermore, a simple ordering-based decision-feedback equalizer （DFE） Was derived to exploit the temperal diversity gain offered by mobile channels. Numerical studies illustrate that although the MMSE equalizer still suffers from error floor, whereas the DICE equalizer exhibits significant performance improvement. The advantage of the proposed scheme indicates its potential applications in the future broadband wireless systems.

A time domain multiple-CFOs and CIRs estimation algorithm over wireless multimedia sensor networks

Channel parameters estimation in an orthogonal for the receiver station is a multi-dimensional （MD） frequency division multiple access （OFDMA） system optimization problem, because every user node has a separate local oscillator and every transmitter to receiver link has individual carrier frequency offset （CFO） and channel impulse response （CIR） parameters. In order to reduce the computational complexity for MD optimization, a time domain CFOs and CIRs estimation algorithm over the OFDMA based wireless multimedia sensor networks （WMSN） is proposed in this paper. In this algorithm, the receiver station can decouple the signal from every node by correlation based on specially designed training sequences, so that the MD optimization problem is simplified to an 1-D optimal problem. It is proved that the multiple CFOs can be identified from the correlation result using the phase shift of the consecutive training se- quences. Based on the CFOs estimation result, the CIRs can then he estimated according to the minimum mean square error （MMSE） criterion. The theoretic analysis and simulation results show that the proposed algorithm can effectively decouple the signal from different user nodes and the bit error rate （BER） per- formance curves are close to the ideal estimation when the user number is not large.

Asymptotic sum rate of MMSE receivers in multi-user distributed antenna systems

In this paper, the asymptotic sum rate of a multi-user distributed antenna system （DAS） is analyzed. To mitigate inter-user interference, minimum mean squared error （MMSE） receivers are utilized to cooperatively process received signals in the uplink. It shows that inter-user interference is efficiently mitigated and the uplink sum rate of a multi-user DAS is greatly improved by adopting MMSE receivers. For very large number of users and remote antennas, the asymptotic uplink sum rate of MMSE receivers is derived by using virtue of the random matrix theory, which can be The approximation is verified to be quite accurate by Monte Carlo simply calculated in an iterative way simulations.

Training sequence based channel estimation for indoor visible light communication system

Channel estimation is a key technology in indoor wireless visible light communications(VLCs).Using the training sequence(TS),this paper investigates the channel estimation in indoor wireless visible light communications.Based on the propagation and signal modulation characteristics of visible light,a link model for the indoor wireless visible light communications is established.Using the model,three channel estimation methods,i.e.,the correlation method,the least square(LS) method and the minimum mean square error(MMSE) method,are proposed.Moreover,the performances of the proposed three methods are evaluated by computer simulation.The results show that the performance of the correlation method is the worst,the LS method is suitable for higher signal to noise ratio(SNR),and the MMSE method obtains the best performance at the expense of highest complexity.

Science Letters:A simplified MMSE-based iterative receiver for MIMO systems

A simplified minimum mean square error(MMSE) detector is proposed for joint detection and decoding of multi-ple-input multiple-output(MIMO) systems.The matrix inversion lemma and the singular value decomposition(SVD) of the channel matrix are used to simplify the computation of the coefficient of the MMSE filter.Compared to the original MMSE detector,the proposed detector has a much lower computational complexity with only a marginal performance loss.The proposed detector can also be applied to MIMO systems with high order modulations.