33results about How to "Improve space coverage" patented technology

The invention discloses a land surface soil moisture downscaling method based on multisource remote sensing satellite merged data and is particularly applicable to cloudy and rainy areas. The method comprises the following steps: collecting and arranging a passive microwave soil moisture data set, an LST (land surface temperature) and NDVI (normalized difference vegetation index) data set and DEM(digital elevation model) data; performing spatial interpolation on LST images with serious pixel deletion affected by cloud and rain by adopting an NDVI and DEM data set as auxiliary data to obtain aday-by-day LST data set almost totally covering a research area; constructing a mathematic relation model for microwave soil moisture with optical remote sensing LST and NDVI by a geographical weighted regression model, and obtaining a land surface soil moisture data set with high spatial resolution with the mathematic relation model. Through the adoption of the method, reliability of a descalingresult and universality of descaling in the wide-range research area are improved effectively, and precision and efficiency of wide-range space mapping and monitoring for soil moisture content in thecloudy and rainy areas are improved.

The invention relates to an MODIS AOD product missing data restoration technology. The technology comprises the following steps of 1, performing preprocessing for remote sensing data of geometric correction, re-projection and the like of MODIS AOD data; 2, verifying the applicability of different levels of DT\DB AOD data; 3, on the basis of increasing spatial coverage degrees of two algorithm products through linear regression equations of DT and DB AOD respectively, performing AERONET precision weighted fusion; 4, further fusing data of two satellites Terra and Aqua by adopting linear regression; and 5, preliminarily restoring residual missing AOD data by adopting a space-time Kriging interpolation method. By utilizing obtained residual errors, a geographically weighted regression model is adopted for further correction, and finally a completely restored AOD data result is obtained. The technology has the beneficial effects that the spatial coverage rate of the AOD data is gradually increased on the premise of guaranteeing AOD data precision, the missing data is completely restored finally, and reliable support is provided for subsequent application.

The invention discloses a monitoring region segmentation method for PM2. 5 inversion and a PM2. 5 inversion method. The monitoring region segmentation method comprises the following steps: with geographic static indexes and PM2. 5 measured concentration in a monitoring region being as samples, summarizing a correlation coefficient of each static index and the PM2. 5 measured concentration; with the correlation coefficient being as weight, carrying out index normalization on each static index to obtain a normalized parameter N_index, wherein the normalized parameter N_index is displayed in theform of raster data; and carrying out multi-scale segmentation on the raster data of the normalized parameter N_index, and determining an optimal segmentation scheme and dividing the monitoring regioninto a plurality of subregions according to the optimal segmentation scheme. The monitoring region is divided through the multi-scale segmentation algorithm, thereby reducing interference of spatialheterogeneity on parameter estimation; and for each of different research subregions, a specific particle concentration inversion model is established.

An antenna including a number of antenna units, each having a lens and an array of beam ports. The antenna units are arranged in a stack, and are configured to transmit or receive signals from the same field-of-view. Each unit is configured to operate in a different frequency band, with the lenses being configured such that an approximately constant beam shape is maintained across the entire operating bandwidth of the antenna.

The invention discloses a sensor network coverage enhancement method based on direction angle decomposition optimization and redundant node removal, and belongs to the field of sensor monitoring. Themethod comprises the following steps: firstly, establishing a three-dimensional cone directed sensing model; decomposing the sensing range of the sensor node into a pitch angle and a deviation angle,and proposing a deviation angle optimization method based on a differential evolution algorithm; and finally, aiming at the problem that a large number of redundant nodes exist in the sensor network,a redundant node removing method is provided. The method can effectively improve the coverage rate of the sensor network and the number of nodes.

The invention discloses a load identification and multi-sensor fusion sensing method and device, and belongs to the technical field of power monitoring, and the method comprises a power monitoring unit which is used for installing one or more intelligent sensors on an existing power grid to carry out the monitoring and collection of current and voltage; information processing: processing the acquired information by using algorithms of different theories; in the sensing fusion process, complete information about electric power is obtained by using a plurality of sensors, and the survival ability of an electric power system is enhanced in the aspects of detection, tracking and electric power identification by using a multi-sensor data fusion technology. Through reasonable control and use of multiple sensors and observation information thereof, redundant or complementary information of the multiple sensors in space or time is combined according to a certain criterion so as to obtain consistent explanation or description of a tested object, data is processed based on NILM, decomposition and analysis of a power grid can be realized, and the reliability of the power grid is improved. And the limitation when load identification is carried out by using the load steady state characteristic information can be overcome to a certain extent.

The invention provides an electronic device. The electronic device comprises an antenna module and a wave-transparent diffraction structure. The antenna module is used for transmitting and receiving electromagnetic wave signals of a preset frequency band in a first direction range. The wave-transparent diffraction structure and the antenna module are arranged at an interval; the electromagnetic wave signals of the preset frequency band are within a first direction range. The first direction range is different from the second direction range, and is used for diffracting the electromagnetic wavesignal incident to the preset frequency band of the wave-transparent diffraction structure, so that the antenna module also receives and transmits the electromagnetic wave signal of the preset frequency band in the second direction range, the first direction range being different from the second direction range. The space coverage of the electromagnetic wave signals of the preset frequency band in the electronic equipment is large, and the communication performance is good.

The invention discloses an antenna device and electronic equipment, and belongs to the technical field of antennas. The antenna device comprises at least one layer of dielectric substrate, a groundingmetal layer, a radiation patch, a first feed structure, a first deflection patch and a radio frequency chip, the grounding metal layer, the at least one layer of dielectric substrate and the radiation patch are stacked. The first feed structure penetrates through the at least one layer of dielectric substrate, a first end of the first feed structure is connected with the radiation patch, a secondend of the first feed structure penetrates through the grounding metal layer and is electrically connected with the radio frequency chip, and a first excitation signal fed by the radio frequency chipis used for exciting a radiation beam of the radiation patch; the first deflection patch is fixed to the first side of the radiation patch. When the radiation patch radiates the wave beam, the deflection of the wave beam radiation direction is realized through different forms (crystalline state and amorphous state) of the first deflection patch, the adjustment of the wave beam radiation directionis realized, and the space coverage of the antenna device is improved.

The invention discloses a fine-modal aerosol parameter inversion method. The characteristic that polarization surface reflectance basically does not change along with wave bands from visible light tonear-infrared wave bands is utilized. The characteristic of small change of polarization surface reflectance is combined. Polarization remote sensing data of the POLDER sensor is inversed to obtain the optical thickness of the fine-modal aerosol. According to the invention, fine-modal aerosol parameters and polarization surface reflectance can be effectively and simultaneously inverted, and the inverted fine-modal aerosol optical thickness has higher spatial coverage, higher spatial resolution and higher precision. The method can be used for researching small-scale fine-modal aerosol, and thecoverage degree and the precision of bright earth surfaces (cities, deserts and the like) are improved.

The embodiment of the invention provides a traffic state monitoring method and a computer program product. In the embodiment of the invention, static attribute data of a monitoring area and dynamic attribute data of the monitoring area within monitoring time can be acquired; performing track identification on the dynamic attribute data to determine a navigation track attribute corresponding to the monitoring area; then, traffic state parameters of road nodes in the monitoring area within the monitoring time can be calculated according to the static attribute data and the navigation track attributes; and the traffic state of the road node in the monitoring time can be determined according to the traffic state parameter of the road node in the monitoring time. In the embodiment of the invention, traffic state monitoring of all road nodes in the monitoring area can be realized based on the static attribute data of the monitoring area and the mining result of the navigation trajectory attribute in the monitoring area, and improvement of the space coverage of traffic state monitoring is facilitated.

A CT detector cell is constructed to have diagonally oriented perimeter walls. With such a construction, the resulting CT detector comprised of such detector cells has improved spatial coverage (spatial density). The number of detector channels is also not increased despite the increase in spatial coverage. Moreover, the detector cells can be constructed without much variance from conventional fabrication techniques.

The invention discloses an optimization processing method for brightness temperature data of a two-dimensional synthetic aperture microwave radiometer, wherein the method comprises the following steps: step 1, respectively obtaining H polarization brightness temperature data and V polarization brightness temperature data of an SMOS according to the brightness temperature data of the SMOS; meanwhile, obtaining SMAP brightness temperature data matched with the SMOS in time and space according to the SMAP brightness temperature data; and step 2, carrying out first nonlinear fitting and second nonlinear fitting according to the brightness temperature data obtained in the step 1, and then completing optimization processing according to translation transformation; or, carrying out the first nonlinear fitting according to the brightness temperature data obtained in the step 1, and completing the optimization processing according to the fixed-point regression fitting. According to the invention, the optimized multi-angle brightness temperature can be obtained, information waste is not caused, and high consistency with the brightness temperature of the SMAP can be maintained. According to the method, the loss of the optimized brightness temperature is less, and the space coverage degree of the SMOS data is greatly improved.

The invention provides a heuristic algorithm for credit assessment feature selection, and the algorithm generates a random spider population based on an SSA algorithm, calculates an opposite solution of the spider population by employing an OBL strategy, selects an optimal solution to form the number of OBL populations, carries out the algorithm iteration of the randomly generated spider population and the OBL spider population, calculates the fitness value and vibration value of a spider individual, selects an optimal solution individual by using a local search algorithm LSA, enables unselected individuals to enter a next round of iteration, and outputs all optimal solutions selected by the LSA after the iteration is finished to form an optimal solution set. According to the invention, the algorithm in the invention is learned through a machine instead of traditional artificial feature screening, so that the efficiency of feature screening is improved; compared with a general heuristic algorithm, an OBL strategy is added into the algorithm, so that the space coverage rate and the stability of the algorithm are remarkably improved; according to the algorithm, an LSA algorithm architecture suitable for the P2P field is introduced, and the feature screening accuracy and the model matching degree are improved.