Patents
Literature
Patsnap Eureka AI that helps you search prior art, draft patents, and assess FTO risks, powered by patent and scientific literature data.

3 results about "Wideband signal processing" patented technology

Radar ranging precision improving method based on high-frequency narrow pulse

PendingCN122085259ARadio wave reradiation/reflectionUltra-widebandCepstral analysis
The invention discloses a radar ranging precision improvement method based on high-frequency narrow pulses, and relates to the technical field of radar ranging and ultra-wideband signal processing, and the method comprises the steps: carrying out the gating interception of a radar receiving sequence, and obtaining an intra-gate sequence; performing cepstrum analysis to determine comb tooth intervals and ripple intensity; constructing a reverse comb ripple frequency domain weight sequence based on the ripple intensity, and performing weighted matched filtering on the intra-gate sequence to extract candidate peaks; calculating sidelobe cluster energy corresponding to the candidate peak according to the comb tooth interval; and calculating a group peak suppression score value based on the ripple intensity and the sidelobe cluster energy, and selecting the candidate peak with the maximum score value as a final peak position to calculate the distance. According to the method, side lobe group peak lifting caused by the wet radome can be inhibited, and the distance measurement precision and stability under the complex meteorological condition are improved.
Owner:HEBEI ZHICHI ELECTRONIC TECHNOLOGY CO LTD

Broadband high-resolution time-frequency analysis and signal sorting method based on photonic processor

In order to solve the problems of wideband signal processing complexity, transient signal difficult to capture and low precision of time-frequency overlapping signal sorting in electronic reconnaissance, a wideband high-resolution time-frequency analysis and signal sorting method based on photonic processor is provided. The method uses optical pulse and cascade modulator to reduce the speed of time sequence decomposition, and completes the delay extraction operation on the optical processor. By matching the bandwidth of the photoelectric detector and the subchannel bandwidth, the filtering operation is realized on the optical processor. In the digital domain, only fractional delay and inverse discrete Fourier transform need to be completed to realize time-frequency decomposition and obtain multiple narrowband reduced speed signals. Parallel short-time Fourier transform is performed on each signal, and due to the reduction of single signal bandwidth, higher time-frequency resolution is obtained under the same processing point number, and finer time-frequency features help to improve the signal sorting and parameter identification precision. The application has low computational complexity and high analysis precision, and is suitable for dense transient signal processing in complex electromagnetic environment.
Owner:SHANGHAI JIAOTONG UNIV

Microwave neural network for broadband signal processing and feature extraction

PCT designated stageWO2026148345A1Nerve networkSpectral bands
A signal modification unit configured for processing high-bandwidth signals includes at least one signal input configured to receive a high-bandwidth signal. The signal modification unit includes a tunable control component configured to adjust one or more parameters for modifying the high-bandwidth signal, wherein the one or more parameters are associated with nonlinear modification of the high-bandwidth signal. The signal modification unit includes one or more waveguide components configured to modify the high-bandwidth signal to generate a modified signal based in part upon the one or more parameters. The signal modification unit includes at least one signal output configured to provide the modified signal as an output of the signal modification unit. The signal modification unit allows for feature extraction of spectral bands and may be used to replace parts of digital neural networks.
Owner:CORNELL UNIVERSITY