11 results about "Basis expansion" patented technology

The application discloses a kind of spectral modulation radiation temperature measuring device and method, belongs to optical radiation temperature measuring technical field.For the problems, such as limited spectral channel, difficult to realize single-exposure multi-channel synchronous acquisition, temperature measuring stability and insufficient inversion robustness of existing radiation temperature measuring technology under long-distance, high dynamic and complex background conditions, the present application sets up wide-spectrum modulation optical window at the incident end, and combines wide-spectrum modulation multi-modal spectral chip, to synchronously acquire multi-channel wide-spectrum modulation radiation image under single exposure;Pretreatment is carried out using system on chip, and wide-spectrum modulation response model, emissivity spectral basis expansion model and time domain regularization are fused in temperature inversion calculation platform, to realize stable inversion of real temperature field, emissivity distribution and temperature rising sequence, suitable for non-contact temperature measurement in long-distance high-temperature target and other fields.

The invention provides a mixed data regression model-based pm2.5 influence factor analysis method and system, and the method comprises the steps: building a mixed data regression model of which covariables are component data and numerical data and dependent variables are functional data: the mixed data regression model is a pm2.5 concentration curve of a city, is the functional data, is the proportion of first yield, second yield and third yield of the city, and is called the proportion of third yield for short; the data is component data, logarithm of per capita GDP, average temperature and numerical data, is a to-be-estimated component type coefficient changing along with time, is distributed to a component type covariable at any moment, is a to-be-estimated function type coefficient and is a function type residual error; obtaining robust M-estimation based on equidistant logarithmic ratio transformation, functional basis expansion and an iterative reweighted least square method; and according to the estimated values, analyzing the influence of the three-yield ratio, the per capita GDP and the average temperature of each city on the pm 2.5. The method can be used for analyzing the pm 2.5 influence factors.

The invention provides a satellite channel estimation method and device and a computer readable storage medium, and the method comprises the steps: determining a compressed sensing measurement matrix based on output samples of N subcarriers and pilot frequency sequences carried by the output samples; utilizing the output samples of the N subcarriers and the compressed sensing measurement matrix to reconstruct an initial input sample matrix; performing multi-scale sparse feature extraction on the initial input sample matrix to obtain a plurality of sparse feature matrixes under different scales; sparse attention calculation is carried out on the sparse feature matrixes of the initial input sample matrix under different scales, and global attention features under corresponding scales are obtained; fusing the global attention features under different scales to obtain a reconstructed target input sample; constructing a basis expansion model of the satellite channel based on the target output sample and the target input sample matrix; and solving the basis expansion model of the satellite channel to obtain the impulse response of the satellite channel. According to the scheme, calculation amount consumption can be reduced, and estimation precision is ensured.

The present invention discloses a channel estimation method for OTFS. For communication in a high-speed mobile environment, the transmission system is a single-input single-output system. A basis expansion model BEM applicable to high-speed mobile scenarios is established according to the sparsity of the channel impulse response. OGCE-BEM is used to fit the OTFS channel. The channel is fitted into the form of basis function coefficients and basis functions. Given the known basis functions, the channel matrix estimation problem is transformed into the estimation problem of basis function coefficients. Then, in the traditional RLS filter algorithm, based on the relationship between the forgetting factor and the estimation error, an iterative update rule based on the forgetting function is designed, improving the real-time tracking ability of the system. The present invention can effectively ensure the effectiveness and reliability of communication, greatly improving the channel estimation accuracy.

The application relates to a Bi-LSTM-SA low-complexity OTFS channel estimation method and system based on a basis expansion model and belongs to the technical field of wireless communication and deep learning. In view of the problems of low channel estimation accuracy and high equalization complexity in a high-speed mobile scene, the application converts time-domain channel estimation into low-dimensional basis coefficient estimation through a basis expansion model, extracts basis coefficient time sequence features by using a self-attention enhanced bidirectional long short-term memory network, and realizes high-precision channel estimation. Meanwhile, a two-stage equalizer is adopted, single-tap equalization is carried out in a time-frequency domain, and residual interference is suppressed through iterative interference cancellation in a delay-Doppler domain. The application effectively balances estimation accuracy and calculation complexity, and improves the anti-Doppler spread capability and spectral utilization efficiency of a system.

The present invention discloses a low-complexity channel estimation method based on user frequency band and simplified basis expansion, which relates to the field of digital communication technology. The method comprises the following steps: obtaining a local time domain signal and extracting a local user frequency band from the local time domain signal; obtaining a frequency domain signal received by a user and extracting a user reception frequency band from the frequency domain signal received by the user; generating basis vectors according to a basis expansion model and performing frequency domain transformation on the basis vectors to obtain a frequency domain transformation matrix; transforming the local user frequency band to obtain a transformation domain symbol A; merging the frequency domain transformation matrices corresponding to all basis vectors to obtain a vector B; multiplying the transformation domain symbol A and the vector B to obtain a solution matrix Q; obtaining a basis coefficient matrix according to the user reception frequency band and the solution matrix; obtaining a time domain channel response matrix according to the basis coefficient matrix, and performing frequency domain transformation on the time domain channel response matrix to obtain a frequency domain channel response matrix. The present invention can provide a channel estimation algorithm with low computational complexity.

A near-optimal Karhunen-Loeve basis expansion modeling (KL-BEM) orthogonal time frequency space (OTFS) receiver with superimposed pilots has been proposed for high-mobility communications with Doppler spread channel. First, an initial KL-BEM channel estimation is conducted by superimposed pilots, followed by the removal of superimposed pilots from the received OTFS signal and equalisation by message passing (MP) algorithm. After that, the detected data symbols are utilized as pseudo pilots along with the superimposed pilots to refine both KL-BEM channel estimation and equalisation in an iterative manner. Simulation results confirm the superior performance of the proposed KL-BEM OTFS receiver over the prior art in terms of the mean-square-error (MSE) of channel estimation and bit error rate (BER). It also has a close BER performance to the BER lower bound obtained by assuming perfect channel estimation. It contributes to high spectral efficiency and fast convergence performance.

The invention belongs to the technical field of wireless communication, and relates to a fast time-varying channel-oriented passive intermodulation interference elimination method, which comprises the following steps of: dividing a signal to be transmitted into a plurality of transmitting signal segments, and adding a training sequence in front of each transmitting signal segment; calculating a time-invariant basis coefficient estimation value of each transmitting signal segment based on a discrete ellipsoid basis expansion model; receiving signal segment sampling values in one-to-one correspondence with the transmitting signal segments are calculated; and calculating the passive intermodulation interference signal of the receiving signal segment based on the time-invariant base coefficient estimation value of the transmitting signal segment and the corresponding sampling value of the receiving signal segment, and subtracting the passive intermodulation interference signal of each receiving signal segment from the receiving signal to realize passive intermodulation interference elimination. The invention also discloses a passive intermodulation interference elimination system for the fast time-varying channel and a terminal. The method can cope with the influence of the time-varying channel, estimates the passive intermodulation interference signal passing through the time-varying channel, and is effectively suitable for passive intermodulation interference elimination under the fast time-varying channel.

The invention relates to an unscented particle filter high-reliability OTFS channel estimation method based on a basis expansion model, and belongs to the technical field of wireless communication. The method comprises the following steps: constructing an orthogonal time-frequency space single-input single-output system transmission model; converting a delay-Doppler domain channel estimation problem into a time domain channel estimation problem; a basis expansion model is adopted to convert a time domain channel estimation problem into a basis coefficient estimation problem; and estimating a basis coefficient and a time domain correlation coefficient by adopting unscented particle filtering so as to track a fast time-varying time domain channel impulse response. According to the method, the calculation efficiency is maintained, the estimation precision and the bit error rate performance are remarkably improved, and the channel estimation precision is improved at the same time.

Pilot symbols and data symbols of a communication frame for an OTFS transmission system are two-dimensionally arranged along the points of a grid in the delay-Doppler domain. The pilot symbols are surrounded by guard symbols. The number of guard symbols in each direction of the Doppler domain is twice the number of the basis expansion modelling (BEM) basis functions used for modelling the communication channel in a receiver, and twice the maximum time delay in terms of delay bins in each direction of the delay domain. The receiver performs an initial pilot-aided channel estimation using BEM of a first BEM order and using the pilot signals, followed by an initial estimation of data symbols using the initial channel estimation, and iteratively performs data aided channel estimation using BEM of a second BEM order and at least the received data signals, until a termination criterion is met.

The invention discloses a wavelet packet-based ultrashort pulse intense laser field higher harmonic voltage detection method and system. The invention relates to the technical field of ultrashort pulse laser detection and analysis. On the basis of a D-S evidence theory algorithm, calculation of information entropy Hi serves as an evaluation index of confidence, decomposition results of different signals under frequency distribution and energy distribution are regarded as different evidences, and basic probabilities (BPA) are distributed; according to the method, the optimal wavelet packet basis expansion can be selected according to frequency distribution and energy distribution of actual signals, so that the wavelet packet decomposition and reconstruction accuracy is improved; the DD-DC neural network model models neurons into a feedback controller of a wavelet packet basis, and an observation result can be directly mapped into a wavelet coefficient, so that a controlled dynamic system does not need to be explicitly represented. The nonlinear compensation strategy can describe the nonlinear characteristics of the signal more accurately. The strategy can capture the characteristics of the signal in the time domain and the frequency domain, and the prediction output is adjusted.