9results about How to "Avoid estimation" patented technology

The present invention discloses a broadband signal direct positioning method based on multi-frequency cost function fusion under unknown attenuation coefficient, including: distributed monitoring nodes receive and sample broadband signals of radiation sources, and transmit the sampled broadband signals to a central site; the central site integrates all received data, performs data preprocessing after segmenting the received data, and obtains narrowband signals corresponding to each frequency in the broadband signal; the covariance matrix of each narrowband signal is characteristically decomposed to obtain its noise subspace, and a new cost function is constructed according to the orthogonal relationship in the multi-band; the positioning area and the search grid size are selected, and a new cost function is adopted, and the gridded spectrum peak search is performed in the selected area in combination with the Lagrange multiplier method when the attenuation coefficient is unknown, and finally the radiation source coordinate estimation value is obtained. The present invention can effectively reduce the time cost required for positioning and effectively improve the estimation accuracy.

The application discloses a deep learning DOA estimation method based on original IQ data. The application uses I and Q components of the original signal as the input of the model to improve the performance. The application aims to solve the DOA estimation problem of a single signal source, and models the single signal source DOA estimation problem as a single-label multi-classification problem. By discretizing the DOA range, the possible directions of arrival are taken as corresponding labels. A convolutional neural network is designed to adapt to different numbers of snapshots, and accurate DOA estimation can be adaptively obtained for input signals of different lengths. Experimental results show that, compared with existing deep learning DOA estimation methods based on covariance matrix as input, the scheme has more excellent performance, and can provide a more reliable solution for array signal processing.

The present invention relates to a federated edge learning gradient aggregation method, device and system in the field of information and communication technology, comprising the following steps: obtaining a training symbol vector, and calculating a beamforming vector based on the training symbol vector; obtaining a transmitted signal in a wireless channel, and calculating a signal matrix based on the transmitted signal; calculating an aggregation gradient based on the beamforming vector and the signal matrix, and calculating a minimized global loss function; updating a global model based on the aggregation gradient and the minimized global loss function, and judging whether the updated global model converges, if converged, terminating, otherwise continuing to update the global model, thereby solving the problem of large communication overhead and loss of learning performance in air-based federated learning channel estimation.

This invention relates to the field of remote sensing image processing technology, specifically to a SAR control point extraction method, apparatus, electronic device, and storage medium. The SAR control point extraction method includes: acquiring multiple SAR images and matched candidate point observation data and imaging geometric parameters; establishing a multi-view positioning observation model; performing initial three-dimensional coordinate calculation to obtain initial calculation results; performing variance component estimation based on prior constraints of imaging geometric configuration to dynamically optimize the observation weights of each image; recalculating the three-dimensional coordinates; iteratively performing weight optimization and coordinate calculation until convergence conditions are met; and selecting and determining SAR control points based on the accuracy index of the final calculation results. This method constructs a robust and complete framework for multi-view stereo SAR control point extraction, embedding geometric prior constraints such as intersection angles and orbit combinations into the variance component estimation process, thus achieving end-to-end optimization processing from candidate corresponding points to high-reliability control points.

The application discloses to the technical field of artificial intelligence, computer vision and deep learning, and particularly relates to an image generation quality evaluation and optimization method based on sparse feedback for industrial design, which comprises the following steps: constructing an industrial design image dataset containing multi-dimensional expert scores; designing a physical flow branch to extract material texture and illumination statistical features, and a semantic flow branch to process picture-text splicing features through a self-attention mechanism; introducing a physical-visual outer product fusion module to capture second-order feature interaction; using the trained evaluation network as a reward model, combining a sparse sampling strategy and a LoRA fine-tuning mechanism, and guiding the diffusion model to align with the industrial design standard under extremely low computing resource consumption. The application significantly improves the material reality, illumination logic and picture-text consistency of the generated image, and provides an efficient and low-cost solution for automatic image generation in the field of industrial design.

The invention belongs to the technical field of risk assessment of malicious instruction attacks in the field of energy control, and particularly relates to an active power distribution network malicious instruction attack risk assessment method considering behavior characteristics. Comprising the steps of establishing a representation model of a non-uniform power distribution network information physical network; according to the representation model, constructing a malicious instruction attack behavior model so as to research the risk that the active power distribution network is attacked by malicious instructions, analyzing the invasion characteristics of the previous malicious instructions, and establishing a numerical simulation model based on historical event data analysis; and constructing a risk assessment model, considering influence factors that information nodes are attacked, and establishing a risk assessment method for the power distribution network under malicious instruction attack threats. According to the method, the evaluation is more comprehensive and accurate through a numerical simulation model of historical event data analysis, the risk value is directly quantified subsequently, the risk can be perceived and measured, the evaluation is more accurate compared with qualitative evaluation, and a targeted defense strategy can be formulated subsequently.

The invention discloses an optimization method and device for InSAR time series phase, including: obtaining a time series SAR data set, and performing L-view processing on the time series SAR data set to obtain an L-view intensity data set and an interference data set respectively; taking the L-view intensity data set as a reference, obtaining and respectively registering and geocoding a preset digital elevation model and a preset land cover map, respectively obtaining a digital elevation in a SAR image coordinate system and a land cover map in a SAR image coordinate system; performing a differential operation on the interference data set according to the digital elevation in the SAR image coordinate system to obtain a differential interference data set; estimating the covariance matrix of the differential interference data set according to the land cover map in the SAR image coordinate system and the differential interference data set, and estimating and obtaining the optimized time series phase according to a preset time series phase maximum likelihood estimation formula. The invention can be applied to a wide range of efficient time series phase optimization estimation processes.

The invention discloses a cross-frequency-point channel spectrum extrapolation method and a cross-frequency-point channel spectrum extrapolation system. Based on an image style migration technology, channel information correlation among different frequency points is ascertained, and channel maps of other frequency points are estimated by utilizing priori knowledge of a channel map of a certain frequency point, so that cross-frequency-point extrapolation is realized. The method comprises the following steps: firstly, modeling a channel map with statistical channel information into a multi-channel image, and combining a cross-frequency point extrapolation problem with an image style migration task; secondly, mining of correlation between frequency points, extraction of prior information features and mapping of a channel map are achieved by designing a generative neural network; further introducing cyclic consistency loss to carry out reciprocal relation fitting; and finally, carrying out fine-grained optimization on an extrapolation result of the channel map through pixel-lattice point conversion. The method not only can realize high-precision extrapolation between any frequency points, but also has relatively strong generalization ability in different wireless communication scenes, and can assist a wireless communication system to realize high-speed transmission.

This application discloses a channel estimation method, apparatus, terminal, network-side device, and medium, belonging to the field of communication technology. The channel estimation method provided in the embodiments of this application includes: a UE receiving first target information from a communication device, the first target information being used to indicate: parameters of a backscatter signal sent by a BSC device, or whether to perform joint channel estimation on a first signal; the UE determining whether to perform joint channel estimation on the first signal based on the first target information; wherein the backscatter signal is obtained by the BSC device modulating the first signal.