7 results about "Asynchronous interference" patented technology

The invention relates to a robust transmitter design method for a large-scale sensor network in a complex environment. The robust transmitter design method is applied to a sensor node transmitter with limited crystal oscillator performance. Comprising the following steps: constructing an uplink asynchronous received signal model of a base station and N sensor terminals, performing maximum ratio combination detection on a received signal, and decomposing the received signal into a target signal, effective noise and multi-symbol asynchronous interference; respectively calculating target signals, effective noise and asynchronous interference energy to construct a signal to interference plus noise ratio model; constructing a codebook optimization problem by taking maximization of a minimum signal to interference plus noise ratio as a target and taking codeword power normalization as a constraint; and optimizing a multi-user codebook in a random asynchronous interference scene based on a DDPG reinforcement learning framework to generate an optimal codebook which meets power normalization constraint and maximizes the minimum SINR, and the optimal codebook is used for symbol coding mapping of a transmitter. The method is adaptive to hardware characteristics of the low-cost sensor, random asynchronous interference introduced by time-varying crystal oscillator offset is effectively resisted, and the reliability of concurrent communication of the low-cost sensor is improved.

The present invention provides a radar co-frequency asynchronous interference suppression method based on slow-time interpolation, the method comprising: extracting sample data sets X of the same range gate Nr received by the radar in the slow-time dimension. Nr_i The sample data group X Nr_i The process involves filtering to identify pulse period sequence group K containing interference signals. j And the pulse period sequence number group K that does not contain interference signals s The interference signal is restored; slow-time dimension sample interpolation is performed to obtain the processed signal X'. Nr_Kj Improve the performance of the radar.

The invention discloses a multi-user detection method and device based on an expansion factor graph and a graph attention network, and the method comprises the steps: carrying out the multi-time oversampling of an asynchronous uplink signal of a receiving end, obtaining a plurality of sampling observations in each symbol period, and constructing the expansion factor graph based on the sampling observations; performing feature extraction on the oversampling receiving signal, and taking a real part and an imaginary part as deep neural network input to obtain node features; and a graph attention network is introduced into the expansion factor graph to carry out information interaction and model training, and a model obtained by training is utilized to judge signals received by each user, so that multi-user joint detection is realized. According to the method, the oversampling signal is modeled into the expansion factor graph structure, and the graph attention mechanism is introduced, so that effective detection of the multi-user signal in the asynchronous SCMA system is realized, and the problems of high multi-user detection complexity and insufficient asynchronous interference resistance in an uplink asynchronous SCMA scene are solved.

The application relates to a kind of air-based asynchronous communication multi-user transmitter design methods, belong to wireless communication technical field, method includes: constructing air-based uplink asynchronous communication system model, base station received signal is characterized as each user time delay and channel weighted codebook coded pulse shaping signal superposition;Received signal is decomposed into target signal, multi-symbol asynchronous interference and effective noise, the signal-to-noise ratio of each user is determined;With the minimum signal-to-noise ratio in all users as the target, with code word power normalization as the constraint condition, the codebook optimization problem of transmitting signal is constructed;Meta-learning algorithm is used to construct task space with time delay information for offline pre-training to obtain meta-model;In the online stage, the current time delay is input, and the adaptive codebook is quickly generated through the meta-model, and the codebook is used for the transmitter to encode the sending symbol to generate the transmitting signal.The application improves the signal-to-noise ratio of multi-user received signal, thereby realizing the reliability of wide-area asynchronous communication of unmanned aerial vehicle.

The application discloses an air traffic control radar narrow pulse interference pulse pressure pre-post combined suppression method, which comprises the following steps: S1, saturation detection and noise accumulation are performed on original data; S2, a bearing-clutter intensity map is established, and clutter cancellation is performed; S3, anti-narrow pulse processing is performed on the pulse cancellation data and original I and Q data in the time domain; S4, step interference detection is performed on the cancellation data, and suspected interference units are marked; S5, suspected interference point confidence evaluation is performed; the confidence of the point in the suspected interference unit window is calculated, the confidence calculation is based on the eigenvalue of the point, and if the calculated confidence is lower than a preset value, the point is discarded. The method effectively solves the influence of clutter on interference detection, performs fine interference detection and suppression according to the characteristics of narrow pulse interference and asynchronous interference, and calculates the confidence of suspected interference points after point condensation, so that the influence of narrow pulse interference on point formation and track association is reduced.

The invention discloses a radar target detection method based on a computer vision dynamic template, and the method comprises the steps: radar video sampling and preprocessing, radar image corrosion based on constant false alarm, radar image smoothing based on gradient information, and finally employing adaptive double-threshold Canny edge detection, and extracting target position and amplitude information based on a detected target. And target detection is completed. According to the scheme, edge extraction is completed under the A display condition, a constant false alarm corrosion algorithm is provided, and weak (sea clutter) and discontinuous (asynchronous interference) targets are inhibited; for radar video echo features, a dynamic template image smoothing threshold and a prior statistical threshold are provided respectively, and the current situation that Canny edge detection Gaussian image smoothing affects edge precision and threshold selection depends on artificial experience dynamic adjustment is solved. And finally, completing edge coordinate transformation, calculating a target center position (centroid point), performing target size and amplitude feature statistics, and realizing target visual feature extraction.

The disclosure relates to a communication technique that merges Internet of things (IoT) technology with a 5th generation (5G) communication system for supporting higher data transmission rates than 4th generation (4G) systems, and a system for same. A method and a device for specifying a cell generating an asynchronous interference are provided. The method includes obtaining base station related information including a location for each base station and received signal strength indication (RSSI) information for each symbol from a base station, identifying whether a cell related to the base station is a cell in which asynchronous interference occurs between cells based on the RSSI information for each symbol, grouping cells in which the asynchronous interference between cells occurs based on the location for each of the base station, determining a type of asynchronous interference between cells, and determining a cell that generates the asynchronous interference between cells.