5results about How to "Prevent inversion" patented technology

The application discloses a power grid carbon emission flow dynamic tracking method based on a physical guided graph neural network, and belongs to the technical field of power system operation analysis and low-carbon dispatching, and comprises the following steps: collecting power grid data in real time and dynamically constructing a power grid topology graph structure; inputting the graph structure into a physical guided graph attention network model trained through a loss function containing physical constraints, wherein the model fuses the edge features of line power and impedance when calculating attention coefficients, so as to infer the carbon potential of all nodes in the network; based on the inferred carbon potential, using a breadth-first search algorithm to start from a load node, tracking and proportionally allocating in the reverse direction along the active power flow path, and determining the carbon emission contribution of the generator set. The application ensures the physical consistency and precision of carbon flow tracking under the condition of lacking real labels, and significantly improves the efficiency of large-scale power grid carbon flow analysis and the adaptability to topology changes.

This application provides a real-time hyperspectral local anomaly detection method and device based on multi-line, multi-band recursive updates. The method includes: acquiring new data blocks for a target scene in real time using a filter array spectral imaging system; updating the current global mean vector and the multi-line, multi-band correlation matrix used for background modeling for the target scene using a recursive update formula to obtain the updated global mean vector and the updated multi-line, multi-band correlation matrix; acquiring the local spatial neighborhood statistics of the new data blocks; and performing local anomaly detection on the new data blocks based on the local spatial neighborhood statistics to obtain the current anomaly detection result data for the target scene. This application can realize local anomaly detection for multi-line, multi-band hyperspectral data and can solve the problems of high computational cost, large storage requirements, and insufficient real-time performance of traditional global covariance matrix calculations in complex industrial backgrounds.

This invention discloses a piecewise adaptive Kalman track tracking method and apparatus based on residual classification, relating to the field of radar track tracking technology. Addressing the problems of poor adaptability to non-stationary measurement noise environments, parameter dependence on human experience, and complex FPGA implementation in existing track tracking methods, this invention proposes introducing a residual classification decision and piecewise adaptive noise adjustment mechanism into the Kalman filter recursive framework. First, a residual vector is calculated based on the predicted state and measurement data. Then, a classification decision is made using the residual vector, the predicted covariance, and the measurement noise covariance of the previous cycle, outputting the measurement quality level. Next, the measurement noise covariance is updated piecewise adaptively based on the measurement quality level. Finally, the filter gain is calculated based on the updated measurement noise covariance and the predicted covariance to complete the correction and update of the state and covariance.

This invention discloses a method for forming nulls in the beam pattern of an array antenna in a specified direction, belonging to the field of electronic defense technology. The method includes the following steps: S1, calculating the weighting coefficients of the signal for each antenna element using an iterative solution method to obtain multiple weighting coefficients; S2, using the multiple weighting coefficients obtained in step S1 to weight the signal passing through multiple antenna elements, thereby forming the main beam of the antenna pattern in the specified direction and simultaneously forming nulls in the antenna beam pattern in other specified directions. Based on this invention, the method can effectively control the null depth in the null direction and achieve the beneficial effect of rapid and effective null beam modulation.

This invention discloses a method for obtaining beamforming weight vectors in an integrated radar-communication system, within the field of array signal processing technology. The method comprises the following steps: S1: Establishing a receiver signal model for a uniform linear array antenna in the integrated radar-communication system; S2: Introducing orthogonal polynomials and the Gauss-Legendal numerical integration method to perform a low-complexity, fast fitting solution for the interference subspace; S3: Introducing the Schmitt orthogonalization method to recursively solve the orthogonal complement projection operator of the interference subspace and project it to obtain the beamforming weight vector; S4: Introducing an equivalent representation of the beamforming weight vector under a dual-phase shifter architecture to obtain the updated beamforming weight vector value under the dual-phase shifter architecture. This beamforming weight vector acquisition method solves the problems of high computational complexity, poor performance in low-quantization-bit hardware scenarios, and desired signal suppression under high signal-to-interference-plus-noise ratios in existing methods, achieving low-complexity and highly robust beamforming.