Abstract: The present invention discloses an urban traffic velocity estimation method based on multi-source crowd sensing data. This method, based on roadside pedestrian data and road navigation data collected by smart phones, obtains a final estimated velocity through the steps of missing data filling, self-view velocity aggregation and multi-view velocity fusion. This fine-grained large-scale urban traffic velocity estimation method can achieve velocity estimation on all types of roads, including suburban road sections and paths, instead of just focusing on main roads in a city center. According to the present invention, based on data driving, the urban traffic velocity estimation method does not need to install additional devices on roads, and is low in cost and high in universality. Compared with the prior art, the urban traffic velocity estimation method has higher practicability, theoretical property and applicability, and is of great significance for improving traffic management and planning.

Abstract: The present invention discloses a human mobility prediction method based on a generative adversarial network. According to the method, the integration of spatio-temporal features of multimodal data is studied by virtue of studying urban human mobility prediction during the pandemic. A human mobility mode is difficult to be predicted during the pandemic due to complex multimodal data such as complicated social background, policy and pandemic situation. The analysis of human mobility data from three cities in China shows that different cities have highly similar human mobility modes during the pandemic, despite of great differences between them. On this basis, the disclosure designs a prediction model, in which the effects of the multimodal data on the spatio-temporal features of the human mobility are modeled integrally. In addition to this, the model can help the government evaluate the potential effects of different policies on human mobility better, and optimize policy development.

Abstract: The disclosure provides a method for estimating a direction of arrival of an L-type coprime array based on coupled tensor decomposition. The method includes: constructing an L-type coprime array with separated sub-arrays and modeling a received signal; deriving a fourth-order covariance tensor of the received signal of the L-type coprime array; deriving a fourth-order virtual domain signal corresponding to an augmented virtual uniform cross array; dividing the virtual uniform cross array by translation; constructing a coupled virtual domain tensor by stacking a translation virtual domain signal; and obtaining a direction of arrival estimation result by coupled virtual domain tensor decomposition.

Abstract: Disclosed in the present invention is a contact tracing pre-screening method for infectious disease susceptible people based on WiFi matching. In the method, based on WiFi connection records of a user and a list of anonymous identification codes of confirmed users collected by a mobile device, a judgment on whether a user has an infection risk is given through the steps of record matching, information compression, dangerous WiFi database construction, coincidence rate calculation between the user and a dangerous WiFi, etc. Data required by this method is easy to be obtained for general smart mobile devices, and no special application program is required. Compared with traditional contact tracing methods based on GPS and Bluetooth, this method provides another dimension of information without using an additional device and sensitive data, has higher operating efficiency, and can help to carry out contact tracing more comprehensively and efficiently.

Abstract: Disclosed in the present invention is a space spectrum estimation method of a super-resolution coprime planar array based on tensor filling of an optimal structured virtual domain, which mainly solves problems that pieces of missing elements in the virtual domain tensor of the existing method are difficult to be filled effectively.

Abstract: Disclosed in the present invention is a contact tracing pre-screening method for infectious disease susceptible people based on WiFi matching. In the method, based on WiFi connection records of a user and a list of anonymous identification codes of confirmed users collected by a mobile device, a judgment on whether a user has an infection risk is given through the steps of record matching, information compression, dangerous WiFi database construction, coincidence rate calculation between the user and a dangerous WiFi, etc. Data required by this method is easy to be obtained for general smart mobile devices, and no special application program is required. Compared with traditional contact tracing methods based on GPS and Bluetooth, this method provides another dimension of information without using an additional device and sensitive data, has higher operating efficiency, and can help to carry out contact tracing more comprehensively and efficiently.

Abstract: Disclosed in the present invention is a two-dimensional direction-of-arrival estimation method for a coprime surface array based on virtual domain tensor filling, which mainly solves the problems of the loss of multi-dimensional signal structural information and the inability to fully utilize virtual domain statistics in the existing method. The steps thereof are as follows: constructing a coprime surface array; modeling a tensor of a received signal of the coprime surface array; constructing an augmented non-continuous virtual surface array based on cross-correlation tensor transformation of the coprime surface array; deriving a virtual domain tensor based on mirror extension of the non-continuous virtual surface array; dispersing contiguous missing elements by reconstructing the virtual domain tensor; filling the virtual domain tensor based on the minimization of a tensor kernel norm; and decomposing a filled virtual domain tensor to obtain a direction-of-arrival estimation result.

Abstract: The present disclosure discloses a three-dimensional co-prime cubic array direction-of-arrival estimation method based on a cross-correlation tensor, mainly solving the problems of multi-dimensional signal structured information loss and Nyquist mismatch in existing methods and comprising the following implementing steps: constructing a three-dimensional co-prime cubic array; carrying out tensor modeling on a receiving signal of the three-dimensional co-prime cubic array; calculating six-dimensional second-order cross-correlation tensor statistics; deducing a three-dimensional virtual uniform cubic array equivalent signal tensor based on cross-correlation tensor dimension merging transformation; constructing a four-dimensional virtual domain signal tensor based on mirror image augmentation of the three-dimensional virtual uniform cubic array; constructing a signal and noise subspace in a Kronecker product form through virtual domain signal tensor decomposition; and acquiring a direction-of-arrival estimation

Abstract: The present invention belongs to the field of array signal processing and relates to a composite tensor beamforming method for an electromagnetic vector coprime planar array. The method includes: building an electromagnetic vector coprime planar array; performing tensor modeling of an electromagnetic vector coprime planar array receiving signal; designing a three-dimensional weight tensor corresponding to a coprime sparse uniform sub-planar array; forming a tensor beam power pattern of the coprime sparse uniform sub-planar array; and performing electromagnetic vector coprime planar array tensor beamforming based on coprime composite processing of the sparse uniform sub-planar array. Starting from the principles of receiving signal tensor spatial filtering of two sparse uniform sub-planar arrays that compose the electromagnetic vector coprime planar array, the present invention forms a coprime composite processing method based on a sparse uniform sub-planar array output signal.

Abstract: Disclosed is a slot-type ultra-wideband depolarized chipless RFID tag. The tag comprises a tag slot unit, a metal plate and a dielectric substrate, wherein the tag slot unit is formed by means of etching the metal plate, and is located on the upper surface of the dielectric substrate; the tag slot unit is composed of at least four annular slot groups, and tags are distributed in a centrosymmetric manner; and each annular slot group is composed of four concentric annular slots that are distributed in a nested manner; a transceiver antenna TX transmits a horizontally polarized electromagnetic wave; a scattered wave obtained; a transceiver acquires a frequency spectrum of the scattered wave; the spectrum is converted into a time-domain signal; a response of the tag is extracted; and an MFCC feature of the time-domain signal is extracted.

Abstract: Disclosed in the present invention is a method for estimating a direction of arrival of a sub-array partition type L-shaped coprime array based on fourth-order sampling covariance tensor denoising, which mainly solves problems of a damage to a signal structure and noise term interference to high-order virtual domain statistics in an existing method. The implementation steps are as follows: constructing an L-shaped coprime array partitioned with linear sub-arrays; modeling a receiving signal of the L-shaped coprime array and deriving a second-order cross-correlation matrix thereof, deriving a fourth-order covariance tensor based on the cross-correlation matrix; realizing fourth-order sampling covariance tensor denoising based on kernel tensor thresholding; deriving a fourth-order virtual domain signal based on denoised sampling covariance tensor; constructing a denoised structured virtual domain tensor; obtaining a direction of arrival estimation result by decomposing the structured virtual domain tensor.

Abstract: The disclosure provides a method for estimating a direction of arrival of an L-type coprime array based on coupled tensor decomposition. The method includes: constructing an L-type coprime array with separated sub-arrays and modeling a received signal; deriving a fourth-order covariance tensor of the received signal of the L-type coprime array; deriving a fourth-order virtual domain signal corresponding to an augmented virtual uniform cross array; dividing the virtual uniform cross array by translation; constructing a coupled virtual domain tensor by stacking a translation virtual domain signal; and obtaining a direction of arrival estimation result by coupled virtual domain tensor decomposition.

Abstract: The present disclosure discloses a method for capturing a trip sign of a turbine due to a high bearing temperature based on correlation and a device therefor. By combining a temperature of a target bearing and related operating parameters thereof, this method can capture possible abnormal trip online. According to the present disclosure, it is not necessary to add additional detection equipment, and it does not need to establish a complex physical model for turbine bearings, and only the historical data of the operating parameters of the temperature of the target bearing and generator set operating parameters related to the temperature of the target bearing are required to complete the establishment of the model for capturing abnormal sign before the trip, which is convenient for popularization and application.

Abstract: Provided is a method of identification and compensation of an inherent deviation of a yaw error of a wind turbine based on a true power curve. The method, based on a wind turbine data acquisition and monitoring control (SCADA) system includes a wind speed, an active power, and a yaw error and so on, runs data in real-time, first pre-processes the data to a certain degree, and then divides a power curve data according to a certain yaw error interval, fits the power curves according to different yaw error intervals through a true power curve fitting flow in connection with an outlier discrimination method, further quantitatively analyzes the different power curves and determines an interval scope of the yaw error inherent deviation value based on an interval determination criterion, and finally compensates the identified inherent deviation value to a yaw error measurement value.

Abstract: Discloses a combined ultra-wideband cross-polarized chipless RFID tag based on MFCC feature coding, which comprises a tag patch unit, a dielectric substrate and a grounding layer, wherein the tag patch unit comprises a barcode-type resonant unit and a double L-type resonant unit; the barcode-type resonant unit consists of five identical rectangular patches arranged in parallel and rotated counterclockwise; the double L-type resonant unit is formed by reversely combining two L-type patches composed of four identical rectangular patches; a transmitting antenna transmits horizontally polarized electromagnetic waves as interrogation signals, the scattered waves reflected by the tag are acquired by a receiving antenna, a receiver acquires the spectrum of the scattered waves to convert the spectrum into time domain signals by inverse Fourier transform, the response of the tag is extracted through a window, and MFCC features are extracted by pre-emphasis and short-time Fourier transform.

Abstract: The present disclosure discloses a three-dimensional co-prime cubic array direction-of-arrival estimation method based on a cross-correlation tensor, mainly solving the problems of multi-dimensional signal structured information loss and Nyquist mismatch in existing methods and comprising the following implementing steps: constructing a three-dimensional co-prime cubic array; carrying out tensor modeling on a receiving signal of the three-dimensional co-prime cubic array; calculating six-dimensional second-order cross-correlation tensor statistics; deducing a three-dimensional virtual uniform cubic array equivalent signal tensor based on cross-correlation tensor dimension merging transformation; constructing a four-dimensional virtual domain signal tensor based on mirror image augmentation of the three-dimensional virtual uniform cubic array; constructing a signal and noise subspace in a Kronecker product form through virtual domain signal tensor decomposition; and acquiring a direction-of-arrival estimation

Abstract: Disclosed is a slot-type ultra-wideband depolarized chipless RFID tag. The tag comprises a tag slot unit, a metal plate and a dielectric substrate, wherein the tag slot unit is formed by means of etching the metal plate, and is located on the upper surface of the dielectric substrate; the tag slot unit is composed of at least four annular slot groups, and tags are distributed in a centrosymmetric manner; and each annular slot group is composed of four concentric annular slots that are distributed in a nested manner; a transceiver antenna TX transmits a horizontally polarized electromagnetic wave; a scattered wave obtained; a transceiver acquires a frequency spectrum of the scattered wave; the spectrum is converted into a time-domain signal; a response of the tag is extracted; and an MFCC feature of the time-domain signal is extracted.

Abstract: The present invention belongs to the field of array signal processing and relates to a composite tensor beamforming method for an electromagnetic vector coprime planar array. The method includes: building an electromagnetic vector coprime planar array; performing tensor modeling of an electromagnetic vector coprime planar array receiving signal; designing a three-dimensional weight tensor corresponding to a coprime sparse uniform sub-planar array; forming a tensor beam power pattern of the coprime sparse uniform sub-planar array; and performing electromagnetic vector coprime planar array tensor beamforming based on coprime composite processing of the sparse uniform sub-planar array. Starting from the principles of receiving signal tensor spatial filtering of two sparse uniform sub-planar arrays that compose the electromagnetic vector coprime planar array, the present invention forms a coprime composite processing method based on a sparse uniform sub-planar array output signal.

Abstract: The invention discloses a method for estimating the direction-of-arrival of a coprime array based on virtual domain statistics reconstruction of single-bit quantized signal. The realization steps are as follows: arranging a coprime array and a single-bit analog-to-digital converter at a receiving end; calculating equivalent virtual signal corresponding to a single-bit receipt signal of the coprime array; constructing a virtual domain augmented covariance matrix of an initialized single-bit quantized signal; designing, based on statistical correlation analysis between statistics of the single-bit quantized signal and the original unquantized signal, an optimization problem based on virtual domain statistics reconstruction of quantized signal; and performing direction-of-arrival estimation by utilizing the virtual domain augmented covariance matrix corresponding to the optimized single-bit quantized signal.

Abstract: The present disclosure discloses a method for capturing a trip sign of a turbine due to a high bearing temperature based on correlation and a device therefor. By combining a temperature of a target bearing and related operating parameters thereof, this method can capture possible abnormal trip online. According to the present disclosure, it is not necessary to add additional detection equipment, and it does not need to establish a complex physical model for turbine bearings, and only the historical data of the operating parameters of the temperature of the target bearing and generator set operating parameters related to the temperature of the target bearing are required to complete the establishment of the model for capturing abnormal sign before the trip, which is convenient for popularization and application.