40 results about "Spatial estimation" patented technology

A method for detecting a loop closure is described. A device accesses pose information and a three-dimensional map of feature points generated by a visual inertia system of the device. The device splits the pose information into a translational part and a rotational part. The device limits the translational part to two-dimensional coordinates and estimates two-dimensional information of the limited translational part based on an accumulator voting space. The device determines an updated pose of the device based on the estimated two-dimensional information, the rotational part, and the three-dimensional map. The pose information is updated with the updated pose.

The invention discloses a method for realizing spatial feature extraction of ionospheric total electron content by using conditional generative adversarial network. In the method, a deep learning model of conditional encoding and decoding generative adversarial neural network with space considerations is firstly designed. The designed model Incorporating an encoder-decoder structure with the idea of ​​adversarial learning, the deep features of the input ionospheric total electron content sampling spatial data and their complex interactions with local structural patterns can be learned. The validity of the method is proved by the example analysis. Compared with the traditional method, this method successfully completes the extraction and restoration of the spatial characteristics of the ionospheric total electron content when faced with complex ionospheric spatial distribution characteristics, and has higher accuracy in realizing the spatial estimation of the ionospheric total electron content and a smaller mean square error.

This disclosure describes electronic video image stabilization techniques for imaging and video devices. The techniques involve determining motion and spatial statistics for individual macroblocks of a frame, and determining a global motion vector for the frame based on the statistics of each of the macroblocks. In one embodiment, a method of performing electronic image stabilization includes performing spatial estimation on each of a plurality of macroblocks within a frame of an image to obtain spatial statistics for each of the macroblocks, performing motion estimation on each of the plurality of macroblocks to obtain motion statistics for each of the macroblocks, integrating the spatial statistics and the motion statistics of each of the macroblocks to determine a global motion vector for the frame, and offsetting the image with respect to a reference window according to the global motion vector.

The invention belongs to the technical field of indoor positioning, and discloses an audio positioning method based on emission angle estimation. At least two base stations with known position information and attitude information are arranged, and each base station is equipped with an array of sound source emitters. The array includes several sound source transmitters that transmit sound signals in different directions; each base station continuously transmits sound signals with identification codes through the sound source transmitters, and the identification codes of the sound signals emitted by different sound source transmitters are uniquely determined and Different from each other; the receiving end receives all sound signals from all base stations, and demodulates the sound signals to obtain the angular probability distribution between the receiving end and the base station; according to the angular probability distribution, the best spatial estimation corresponding to the receiving end and each base station is obtained Angle: According to the best spatial estimation angle in the base station coordinate system, the position information and attitude information of the base station, the spatial position of the receiving end is obtained. The invention solves the problem of low accuracy of indoor positioning.

The invention belongs to the technical field of array signal processing and provides a multiple signal classification method based on a Sigmoid covariance matrix. This method has a strong ability to suppress impulsive noise that obeys non-Gaussian distribution, and can realize multiple signal classification under the impulsive noise condition, and estimate the direction of arrival of each signal; including: 1) According to the noise-containing The median of the signal amplitude estimates the parameters of the Sigmoid function; 2) uses the Sigmoid function and the output vector of the uniform linear array to estimate the Sigmoid covariance matrix output by the array; 3) performs eigenvalue decomposition on the Sigmoid covariance matrix to obtain the noise sub- Space estimation: use the noise subspace to estimate the spatial spectrum for multiple signal classification, and use the estimated value of the spatial spectrum to estimate the direction of arrival angle. The algorithm of the invention has good performance and has good application prospect in real engineering applications.

The invention discloses a Beidou satellite signal high-precision blind capture method based on wavelet transform. The method comprises the steps that S1 a satellite signal is collected, and backgroundnoise reduction is carried out on a sampled signal through a wavelet threshold noise reduction method to acquire a noise-reduced sampled signal; S2 a model is established for the satellite signal received by a satellite receiver, and the model is converted into a single-input and multiple-output blind disjunctive model, and the noise-reduced sampled signal is used as the input signal of the blinddisjunctive model; S3 the blind disjunctive model is used to construct a new spatial spectral function, and the spatial spectral function is searched to acquire the frequency of the satellite signal;and S4 the initial phase of the signal is solved according to the frequency of the satellite signal to complete satellite capture. According to the invention, the blind disjunctive model and the wavelet transform theory are combined; a satellite signal blind separation method based on a subspace estimation algorithm is used to solve the Doppler effect frequency and phase of the Beidou satellite signal; and the method has the advantages of strong anti-noise ability, stable performance and high precision.