谱传感--基于知识驱动的无线电监管

当前,我国无线电管理的总体要求是"管资源、管台站、管秩序,服务经济社会发展、服务国防建设、服务党政机关,突出做好重点无线电安全保障工作"。为达到上述要求,需要通过获取多维数据得出完备的知识,作为无线电监管科学决策的支撑。本文论述了一种利用谱传感获取多维数据,经信息加工后,以知识驱动的方式达到无线电监管要求的方法。

极谱氧传感仪测定SOD快速诊断先天愚型及其产前诊断的研究

应用极谱氧传感检测仪，测定红细胞中的ＳＯＤ活性来鉴定Ｄｏｗｎ＇ｓ，探索替代传统的染色体诊断方法。本文检测６２例健康人红细胞的ＳＯＤ为６９３５±４８７ｕ／ｍｌ，３２例Ｄｏｗｎ＇ｓ红细胞的ＳＯＤ为１０６０２±８２９ｕ／ｍｌ。而检测４８例健康新生儿红细胞的ＳＯＤ为５６２７±４６３ｕ／ｍｌ，３６例健康胎儿红细胞的ＳＯＤ为５７０７±４７５ｕ／ｍｌ，５例Ｄｏｗｎ＇ｓ新生儿红细胞的ＳＯＤ为８３０７±２２９ｕ／ｍｌ。研究结果显示Ｄｏｗｎ＇ｓ比健康人的红细胞ＳＯＤ高１．５倍，两者具有显著性差异。本方法检测快速，只需５０分钟，灵敏度高，操作简便，具有实用推广价值。

谱能量传感及USRP实现

谱传感是认知无线电和下一代通信网络的基础,基于蒙特卡诺方法,构造了谱能量传感的数学模型,仿真了典型信道条件下谱能量传感的性能,并分析了相应信道条件下虚警率、信噪比、检测时间与检测率之间的关系。同时,利用软件无线电设备USRP实现了谱能量传感,验证了其性能。

超声波焊接埋入镍基光纤光栅的温度传感

超声波金属焊接具有低温、低压及低能耗的加工优点,可用于埋入智能单元光纤布拉格光栅传感器(FBG),制备3D智能金属结构。而在埋入金属基体过程中FBG易应力失效。采用复合镀镍方法对FBG进行预保护,基于金属化FBG(MFBG)使用超声波焊接工艺埋入至厚度300μm的AA6061铝基体中,以获得3D智能金属结构。结果表明:超声波焊接下MFBG可埋入铝基体中;对超声波焊接制备的3D智能金属结构进行了温度传感与透射谱检测分析,温度灵敏度提高了1倍多,且温度传感线性度较好,有效抑制了温度交叉敏感性;埋入铝基体后FBG谐振谱布拉格峰出现了蓝移与峰值损耗降低。

基于蒙特卡洛方法的频谱能量检测研究

频谱传感是下一代无线通信网络的基础。基于蒙特卡洛方法,建立了频谱能量检测的数学模型,仿真了典型信道条件下频谱能量检测的性能,并分析了相应信道条件下虚警率、信噪比、检测时间与检测率之间的关系,以及Log-Normal信道下标准差对检测率的影响。结果表明:仿真结果与理论一致,增加观察时间、提高信噪比或采用分集技术都有利于提高检测率;与理论方法比较,蒙特卡洛方法具有通用性,适用于更复杂的信道情况。

An Open-Loop Test of a Resonator Fiber Optic Gyro

The resonator fiber optic gyro （R-FOG） ,which utilizes a resonance frequency change due to the Sagnac effect,is a promising candidate for the next generation inertial rotation sensor. In this study, an open-loop R-FOG is set up using phase modulation spectroscopy. First,the demodulation curve is obtained using a lock-in amplifier. From the demodulation signal,a gyro dynamic range of ± 4.2rad/s is obtained. Then,using different phase modulation frequencies,the open-loop gyro output signal is measured when the gyro is rotated clockwise or counterclockwise. The bias drift as a function of time is also measured. The fluctuation of the output over 5s is about 0.02rad/s. The drift can be reduced by taking countermeasures against system noise.

Investigation of prior image constrained compressed sensing-based spectral X-ray CT image reconstruction

To improve spectral X-ray CT reconstructed image quality, the energy-weighted reconstructed image xbins^W and the separable paraboloidal surrogates（SPS） algorithm are proposed for the prior image constrained compressed sensing（PICCS）-based spectral X-ray CT image reconstruction. The PICCS-based image reconstruction takes advantage of the compressed sensing theory, a prior image and an optimization algorithm to improve the image quality of CT reconstructions.To evaluate the performance of the proposed method, three optimization algorithms and three prior images are employed and compared in terms of reconstruction accuracy and noise characteristics of the reconstructed images in each energy bin.The experimental simulation results show that the image xbins^W is the best as the prior image in general with respect to the three optimization algorithms; and the SPS algorithm offers the best performance for the simulated phantom with respect to the three prior images. Compared with filtered back-projection（FBP）, the PICCS via the SPS algorithm and xbins^W as the prior image can offer the noise reduction in the reconstructed images up to 80. 46%, 82. 51%, 88. 08% in each energy bin,respectively. M eanwhile, the root-mean-squared error in each energy bin is decreased by 15. 02%, 18. 15%, 34. 11% and the correlation coefficient is increased by 9. 98%, 11. 38%,15. 94%, respectively.

Energy-aware cooperative spectrum sensingfor underground cognitive sensor networks

With the development of wireless technologies,multifarious standards are currently used in the underground coal mine communication systems.In this paper,the coexistence of 802.15.4 based wireless senser networks （WSNs） with other wireless networks using cognitive radio technique are discussed.Multiple sensor nodes are involved in the spectrum sensing to avoid the interference from other wireless users.The more the sensor nodes cooperate in the sensing,the better the detection performance can be obtained; however,more energy is consumed.How to get the tradeoff between energy efficiency and detection performance is a key problem.According to the requirements for detection,we first give the least required detection time of a single sensor node.Then,the voting fusion rule is adopted for the final decision making.Finally,the relationship between final detection performance and energy consumption is analyzed.

Space-Time Correlation Based Fast Regional Spectrum Sensing in Cognitive Radio

In this paper,a space-time correlation based fast regional spectrum sensing(RSS)scheme is proposed to reduce the time and energy consumption of traditional spatial spectrum sensing. The target region is divided into small meshes,and all meshes are clustered into highly related groups using the spatial correlation among them. In each group,some representative meshes are selected as detecting meshes(DMs)using a multi-center mesh(MCM)clustering algorithm,while other meshes(EMs)are estimated according to their correlations with DMs and the Markov modeled dependence on history by MAP principle. Thus,detecting fewer meshes saves the sensing consumption. Since two independent estimation processes may provide contradictory results,minimum entropy principle is adopted to merge the results. Tested with data acquired by radio environment mapping measurement conducted in the downtown Beijing,our scheme is capable to reduce the consumption of traditional sensing method with acceptable sensing performance.

Influence of stress birefringence on the performance of a FBG pressure sensor

The effects of using overall affix and two-spot affix between the FBG and underlay on the characteristics of the pressure sensors are compared both experimentally and theoretically.It is found that overall affix can produce large nonlinear effect on the characteristics of output of the sensors.The nonlinear effect caused by the expanded spectral width mainly due to the stress birefringence and the stress grads etc.The experimental result shows that the spectral width caused by using overall affix is 0.28 nm and the linearity can have up to 1.89% of increasing by using two-spot affix.The method of two-spot affix can improve response characteristics of the sensor which is benefit to achieve wavelength demodulation and to improve measurement precision.

Turbidity measurement based on a multi-wavelength spectral sensor

A method of measuring turbidity based on a multi-wavelength spectral sensor is proposed by using SFH4737 broad-band infrared LED,a multi-wavelength spectral sensor and independently developed data processing software.Combining multiple wavelength data from the sensor,the unitary and multivariate fitting models were constructed to investigate the relationship among light intensity information,absorbance and turbidity,respectively.The turbidity of the actual water bodies was measured separately by using proposed method and a commercially visible spectrophotometer.The independent-samples T test(p>0.05)showed that there was no significant difference between the method in this paper and the standard assay method.The method is simple and inexpensive,and can be applied to the rapid detection of water turbidity,providing a new way of industrial online measurement.

Sensing characteristics of a metal film coated long-period fiber grating

To obtain the influence rules of the coating parameters of a long-period fiber grating(LPFG)with respect to temperature,strain and refractive index sensing properties,based on the mode coupling theory,a strict four-layer theorietical model of a metal film coated LPFG is established,and these parameters that affect the spectral characteristics of the metal film coated LPFG are studied.The simulation results show that there is an optimal metal film thickness on the surface of the LPFG that will induce the surface-plasmon resonance(SP R)effect,which results in higher sensitivity to the environmental temperature and refractive index but has little influence on the strain There is theoretical evidence that when the silver thickness is between0.8and1.2nm,the refractive index sensitivity will reach the peak point of42.4026,at which the refractive index sensor sensitivity is increased by4.S%.The theoretical results of coating a long-period fiber grating provide a good theoretical basis and guidance for LPFG design and parameters optimization

Degradation of Antibiotics in Aqueous Solution by Photocatalytic Process： Comparing the Efficiency in the Use of ZnO or TiO2

The study examined the photodegradative efficiency of ZnO and TiO2 in degradation of antibiotics in aqueous matrices. Among several types of antibiotics, four antibiotics were chosen to feature the major classes of these compounds： amoxicillin, erythromycin, streptomycin and ciprofloxacin. Degradation of antibiotic solutions was carried out mainly under UV-light irradiation in a set time with the presence of small quantity of zinc oxide or titanium dioxide. Solutions were analyzed with HPLC chromatography and degradation percentages were calculated from ratio between pick area associated to no degraded drug solution and degraded drug solution＇s pick area. Meanwhile, toxicity of antibiotics and degrading compounds were investigated using a biosensor system, consisting of Clark＇s electrode associated with a portion of agar medium culture containing Saccharomyces Cerevisiae yeast cells. This way, it was possible to define the oxygen that was consumed by yeast cells. Toxicity associated to antibiotics and degrading products are related to decrease of oxygen concentration in solution. It is clear that zinc oxide is slower than titanium dioxide to degrade antibiotics, but zinc oxide shows better photodegradation efficiency than titanium dioxide in spite of its small specific superficial area.

Traffic sensitive spectrum access scheme for cognitive radio networks

A traffic sensitive spectrum access scheme is proposed to satisfy the traffic load requirement of secondary users （SUs）. In the proposed design, SU only accesses available channels which can meet the traffic demand. To achieve this, the expected transmission time （E3W） of the SU is calcu- lated first based on the delivery ratio. Then, the channel idle time is estimated based on the activity of primary users （PUs）. Therefore, available channels with estimated idle time longer than ETr could be chosen. With high probability, the SU can finish transmission on these channels without disruption, thereby satisfying the traffic load demand of the SU. Finally, our method is extended to the multi-channel scenario where each SU can access multiple channels simultaneously. Performance analysis shows that our method satisfies the requirement of SUs while effectively improving the throughput.

Optimal Spectrum Sensing in Energy Harvesting Cognitive Radio Systems

In this paper,we consider a cognitive radio system with energy harvesting,in which the secondary user operates in a saving-sensing-transmitting(SST) fashion.We investigate the tradeoff between energy harvesting,channel sensing and data transmission and focus on the optimal SST structure to maximize the SU's expected achievable throughput.We consider imperfect knowledge of energy harvesting rate,which cannot be exactly known and only its statistical information is available.By formulating the problem of expected achievable throughput optimization as a mixed-integer non-linear programming one,we derive the optimal saveratio and number of sensed channels with indepth analysis.Simulation results show that the optimal SST structure outperforms random one and performance gain can be enhanced by increasing the SU's energy harvesting rate.

Design of a Weak Signal Detecting Circuit in the Infrared Spectrum Absorbed Type Gas Sensor

In the infrared spectrum absorbed type gas concentration sensor,voltage signal obtained from the two-channel thermopile infrared detector TPS2534 is very weak.In order to solve this problem,the authors have established the structure of the sensor and designed weak signal detecting circuit of the sensor based on infrared spectrum absorption principle,differential de-noising principle and weak signal detecting principle.The authors have made experiments using CH4 gas.The results show that the circuit can remove noise effectively and detect weak electrical signal obtained from the detector.

Room temperature gas sensor based on tube-like hydroxyapatite modified with gold nanoparticles

The main goal of this work is to explore the possibility of using Au-modified hydroxyapatite(HA) as a potential sensor material. Tube-like HA structure was fabricated with the aid of a Nafion N-117 cation exchange membrane and gold(Au) nanoparticles were added by a hydrothermal method. The morphology, structure and composition were characterized by scanning electron microscopy(SEM), transmission electron microscopy(TEM), X-ray diffraction(XRD), and X-ray photoelectron spectroscopy(XPS). The gas sensing properties were also investigated. Results show that Au nanoparticles are dispersed into the HA powder, which is tube-like, with rough inner and outer surfaces. Compared with pure HA, Au-modified HA exhibits improved sensing properties for NH_3. 5%(mass fraction) Au-modified HA shows the highest response with relatively short response/recovery time. The response is up to 79.2% when the corresponding sensor is exposed to 200×10^(-6) NH_3 at room temperature, and the response time and recovery time are 20 s and 25 s, respectively. For lower concentration, like 50×10^(-6), the response is still up to 70.8%. Good selectivity and repeatability are also observed. The sensing mechanism of high response and selectivity for NH_3 gas was also discussed. These results suggest that Au-HA composite is a promising material for NH_3 sensors operating at room temperature.

Development and Potential of Space-Borne Doppler Wind Lidar

The advantage of lidar over other wind sensors is presented in this paper. With more than 20 years research, the development of the space-borne wind lidar is reviewed. Longer-term investigation has made many technologies suitable for the wind lidar measurement from an orbital platform become mature. However, there are still some problems to be solved. In order to obtain the optimal performance in wind detection, great importance is being attached to the simulation of a virtual space-borne wind lidar system on computer as developed by NASA and ESA.

The Monitoring of Red Tides Based on Modular Neural Networks Using Airborne Hyperspectral Remote Sensing

This paper proposes a red tide monitoring method based on clustering and modular neural networks. To obtain the features of red tide from a mass of aerial remote sensing hyperspectral data, first the Log Residual Correction （LRC） is used to normalize the data, and then clustering analysis is adopted to select and form the training samples for the neural networks. For rapid monitoring, the discriminator is composed of modular neural networks, whose structure and learning parameters are determined by an Adaptive Genetic Algorithm （AGA）. The experiments showed that this method can monitor red tide rapidly and effectively.

Highly Effective Detection of Amitraz in Honey by Using Surface-Enhanced Raman Scattering Spectroscopy Coupled with Chemometric Methods

As an effective and universal acaricide, amitraz is widely used on beehives against varroasis caused by the mite Varroa jacobsoni. Its residues in honey pose a great danger to human health. In this study, a sensitive, rapid, and environmentally friendly surface-enhanced Raman spectroscopy method (SERS) was developed for the determination of trace amount of amitraz in honey with the use of silver nanorod (AgNR) array substrate. The AgNR array substrate fabricated by an oblique angle deposition technique exhibited an excellent SERS activity with an enhancement factor of -10^7. Density function theory was employed to assign the characteristic peak of amitraz. The detection of amitraz was further explored and amitraz in honey at concentrations as low as 0.08 mg/kg can be identified. Specifically, partial least square regression analysis was employed to correlate the SERS spectra in full-wavelength with Camitraz to afford a multiple-quantitative amitraz predicting model. Preliminary results show that the predicted concentrations of amitraz in honey samples are in good agreement with their real concentrations. Compared with the conventional univariate quantitative model based on single peak’s intensity, the proposed multiple-quantitative predicting model integrates all the characteristic peaks of amitraz, thus offering an improved detecting accuracy and anti-interference ability.