31results about How to "Lower SNR Threshold" patented technology

The invention discloses a meter-wave radar low elevation estimating method based on a minimum redundancy linear sparse submatrix. The meter-wave radar low elevation estimating method based on the minimum redundancy linear sparse submatrix mainly solves the problem that errors of estimation of meter-wave radar low elevations are large in the prior art. The meter-wave radar low elevation estimating method based on the minimum redundancy linear sparse submatrix comprises the implementation steps of (1) structuring a minimum redundancy linear sparse submatrix meter-wave radar, (2) extracting target signals from radar echoes, (3) calculating auto-covariance matrixes of submatrixes and cross covariance matrixes among the submatrixes, (4) structuring an augmented matrix of whole array data covariance matrixes, (5) restoring the rank of the augmented matrix by applying a spatial smoothing algorithm of distributed submatrixes, (6) carrying out characteristic decomposition on the covariance matrixes to obtain signal subspaces, (7) obtaining direction cosine non-fuzziness coarse estimation, (8) obtaining direction cosine fuzziness fine estimation, and (9) solving the fuzziness of the fine estimation by using the coarse estimation to obtain low elevation estimation with high precision and without fuzziness. According to the meter-wave radar low elevation estimating method based on the minimum redundancy linear sparse submatrix, the aperture of the meter-wave radar is expanded, the threshold of the signal to noise ratio is lowered, the precision of the lower elevation estimation is improved, and the method can be used for positioning and tracking targets.

The invention belongs to the technical field of radar signal detection and evaluation, and particularly relates to a QFM signal parameter evaluation method based on a four-order asymmetrical product type kernel function. The method includes the steps of firstly, calculating the initial signal energy, setting a circulation initial value and establishing a matrix used for storing all subsequent component parameter estimation values; secondly, multiplying the time delay function of the four-order asymmetrical product type kernel function with the conjugation time delay function of the four-order asymmetrical product type kernel function, and conducting phase matching and converting on phases of the four-order asymmetrical product type kernel function, wherein the estimation values of the second parameters of the signal components can be obtained in the positions of frequency domain peak values; thirdly, constructing a new four-order asymmetrical product type kernel function for signals with compensation conducted on the second parameter estimation values, and conducting fast Fourier transform to obtain a frequency-frequency change rate two-dimensional distribution diagram, wherein third parameter estimation values and third parameter estimation values of the signal components can be obtained from the positions of the peak values; fourthly, filtering the signal components, estimated in the steps, out of the signal; fifthly, resetting cyclic variables and a signal, and calculating the ratio of the total energy of the signal to the initial signal energy.

The invention relates to an adaptive turbo equalization method, an equalizer and an underwater acoustic communication system. The method comprises the following steps: calculating a primary symbol estimated value (the formula is as shown in the specification) according to a received symbol sequence r (i) and a priori symbol mean vector (the formula is as shown in the specification); calculating a symbol estimated value (the formula is as shown in the specification) fed back by a prior variance according to the primary symbol estimated value (the formula is as shown in the specification) and a prior symbol variance v (i); and calculating an output log likelihood ratio LLR of each symbol according to the symbol estimated value (the formula is as shown in the specification) fed back by the prior variance. The priori symbol information is mapped to obtain a priori symbol mean and a priori symbol variance. According to the adaptive turbo equalization method provided by the invention, the priori symbol information output by an SIOS decoder is better utilized, the communication performance under time-varying multipath is improved, and the signal to noise ratio threshold is reduced.

A method and system for burst frame detection and timing synchronization based on the Wi-SUN system, the method adds peak combining and peak-to-average ratio calculations in cross-correlation burst frame detection, and reduces the signal-to-noise ratio of burst frame detection threshold. The present invention uses the repetition and inversion characteristics of the short preamble to construct a specific local correlation sequence, and converts the conventional timing correction method of multi-peak maximum evaluation into single-peak timing estimation, so that the system can avoid multiple The problem of main and auxiliary peak position exchange caused by peak noise interference improves the reliability of timing calibration and provides broader working conditions for the subsequent precise timing and frequency offset adjustment of long pilot sequences.

The invention discloses a method and a device for estimating a frequency ramp and a frequency deviation in a satellite mobile communication system. The method comprises the following steps of: according to parameters of an actual communication system, obtaining a range of a normalized frequency ramp value aD and calculating a trial interval delta aD of the frequency ramp value; carrying out repeated test on the normalized frequency ramp value aD by utilizing a frequency deviation estimating method, wherein the test interval each time is delta aD, one or a plurality of (aD, fD) number pairs are obtained in each trial process, and a set is formed by all the (aD, fD) number pairs after all the test processes are completed; and substituting all the (aD, fD) number pairs in the set into a likelihood function G (aD, fD), searching the (aD, fD) number pair capable of ensuring the likelihood function to attain the maximum value and using the (aD, fD) number pair as estimation values of the frequency ramp and the frequency deviation. The method and the device have the advantages of low SNR (Signal to Noise Ratio) threshold, low computational complexity and high estimation accuracy. In the actual application, the existing module can be continuously used in the method for estimating the frequency deviation, the estimation on the frequency ramp can be realized without great improvement, and the method and the device are very convenient.

The invention belongs to the field of digit signal processing, and provides an improved frequency estimation method and device for all-phase time-shift phase difference, capable of improving precision and robustness and lowering signal-noise ratio threshold. The frequency estimation method includes the steps of inputting M=2N-1+L samples, namely x(-N+1-L) to x(N-1), obtaining a first path phase value phi, conducting all-phase FFT for x(-N+1-L) to x(N-1), directly taking the phase of index value K=K2 at peak spectrum as a second path phase value phi2, multiplying the difference of two paths of phase value (phi-phi2) with 1 / delta omega L to obtain the initial frequency bias estimated value epsilon, conducting frequency drift compensation for the initial frequency bias estimated value epsilon to obtain the modified frequency bias estimated value ^ epsilon, and outputting the normalized frequency estimated value as described in the description. The method and apparatus are applicable to digital signal processing.

The invention relates to an improved Wiener filter and a method for estimating target azimuth based on the filter. Combined with the ability of a beamformer to suppress noise in the space domain and the improved ability of the Wiener filter to suppress noise in the time domain, it proposes that the received data First, by improving the Wiener filter, a certain gain is obtained in the time domain, and then the target azimuth estimation is obtained through the beamformer. This method is called beamforming after tradeoff filter (BATF). By controlling the parameters of the improved Wiener filter, the signal distortion and noise suppression are effectively controlled, so that the output signal of the improved Wiener filter is within the range of the beamformer's tolerance to signal distortion, thereby obtaining the best output, and making The root mean square error of target bearing estimation is reduced, the signal-to-noise ratio threshold of target bearing estimation is lowered, and the problem that the performance of target bearing estimation is degraded under low signal-to-noise ratio of existing methods is overcome.

The invention belongs to the technical field of digital communication and particularly relates to a stochastic resonance and wavelet transform combined symbol rate estimation method and device under alow signal to noise ratio condition. The method comprises the steps of carrying out digital sampling on sending signals in a channel, thereby obtaining high power sampled signals; shifting spectrum of the high power sampled signals to intermediate frequency, obtaining intermediate frequency signals, and determining bistable stochastic resonance system parameters; and carrying out iterative processing on the intermediate frequency signals through a bistable stochastic resonance system; carrying out wavelet transform on the signals after the iterative processing; and calculating modulus spectrum for the signals after the wavelet transform, and obtaining symbol rate estimation through observation of peak positions. According to the method and the device, influences that an effect is poor anda wavelet scale is difficult to determine when stochastic resonance is employed independently are compensated, the accurate estimation for symbol rates of weak MPSK and MQAM intermediate frequency signals under a low signal to noise ratio is realized. A simulation experiment shows that output peaks are improved to a certain degree, a signal to noise ratio threshold is reduced, and the method andthe device are significant in the symbol rate estimation under the low signal to noise ratio.

The invention belongs to the acoustic vector sensor array signal processing field, and more specifically relates to an acoustic vector circular array source number detection method based on characteristic value multiple threshold correction which is applied to underwater target remote passive detection. The method comprises establishing an acoustic vector circular array signal receiving model, obtaining acoustic vector circular array receiving acoustic pressure data, radial vibration velocity data and tangential vibration velocity, constructing a covariance matrix of acoustic vector circular array acoustic pressure and vibration velocity combined treatment, and decomposing characteristic values; and performing multiple threshold division treatment on a characteristic value set obtained by decomposing the covariance matrix to obtain a signal and noise corresponding characteristic value set. The method dynamically integrates an information theory detection method based on characteristic value multiple thresholds and the sound anti-noise performance of an acoustic vector circular array, obviously reduces the signal to noise ratio threshold of a detection algorithm, and overcomes the disadvantages that traditional detection methods such as MDL, diagonal loading MDL, and GDE are more sensitive to noise characteristic value change.

The invention belongs to the field of communication technology, and particularly to a weak OFDM subcarrier number estimation method based on random resonance. The method comprises the steps of settinga sampling frequency, wherein the sampling frequency is N times of a lowest sampling frequency, wherein N is not less than 50; selecting a bistable random resonance system parameter; for aiming at asignal which passes a bistable random resonance system, calculating a cepstrum and / or performing Haar wavelet transformation, and calculating an actual subcarrier number. The method of the invention is based on a cepstrum method and a wavelet improvement method. A random resonance method is used for reinforcing the weak OFDM signal. Compared with a traditional method, the weak OFDM subcarrier number estimation method has advantages of increasing an output peak value, improving detecting performance, reducing signal-to-noise ratio threshold, exerting an advantage on the condition of severe channel environment, improving estimation precision, improving algorithm performance for estimating the number of OFDM signal subcarriers to a relatively high extent, performing certain advantage on the condition of low signal-to-noise ratio, realizing better effectiveness and robustness, and performing an important function for restoring information of the OFDM signal on the condition of low signal-to-noise ratio, etc.

The present invention provides a maneuvering target detection method based on time-frequency analysis, comprising the following steps: acquiring a radar echo signal of a sky-wave radar within a first position range as a first radar echo signal, wherein the radar echo signal contains a maneuvering target Echo: Phase transformation is carried out to the first radar echo signal to obtain the second radar echo signal; by performing matching Fourier transform on the instantaneous frequency change rate of the maneuvering target to the second radar echo signal at different times respectively, Obtain a joint domain based on time and instantaneous frequency rate of change; in the established coordinate system with time and instantaneous frequency rate of change coordinate axes, along the straight line parallel to the time coordinate axis corresponding to different instantaneous frequency rate of change, the Integrating the joint domain to obtain the accumulated energy function of the maneuvering target; judging whether the energy function is less than a preset energy threshold; when the energy function is greater than or equal to the energy threshold, determining that the maneuvering target is within the first position range.