384 results about "Real signal" patented technology

A processing device and method for an error adjustment system for equalizing transmission characteristics of N signal processing circuitries according to N signal branches (N>1) are disclosed. An original complex IQ signal of a signal branch of N signal branches and a processed real signal of the signal branch are received. A processed complex IQ signal of the signal branch is calculated from the processed real signal and the original complex IQ signal of the signal branch. Then, a difference between the processed complex IQ signal and the original complex IQ signal is calculated. Finally, control values of a correction function of the signal branch are calculated on the basis of the calculated difference. The calculated control values are supplied to the correction function of the signal branch. The receiving, calculating and supplying operations are performed for all N signal branches.

Different from conventional equalizers, the output of an SAIC (Single Antenna Interference Cancellation) linear equalizer in GSM/EDGE wireless communication systems is a real signal combined from two real FIR (Finite Impulse Response) filter outputs. Each of the FIRs separately uses the real and imaginary components of the ½π de-rotated received signal as input. The real-valued output of the SAIC equalizer creates difficulty to estimate and correct the frequency errors due to receiver LO and Doppler shift. Disclosed is an efficient and effective solution to the estimation and correction of the frequency error through an assistant signal generated by two additional FIR filters. The assistant signal and the SAIC equalizer output are used to estimate the frequency error, which is combined with the SAIC equalizer output and the assistant signal to give the frequency error corrected SAIC equalizer output.

The invention provides a method for judging the pollution of a dust sensor, a wiping system and a cleaning robot thereof. The dust sensor comprises a pair of optical signal elements, wherein the pair of optical signal elements are arranged at both sides of a dust passage and respectively used for transmitting and receiving optical signals; and one sides of the optical signal elements, which are close to the dust passage, are respectively provided with a transparent plate used for keeping dust out and protecting the dust sensor. The method for judging the pollution of the dust sensor comprises the following steps of: carrying out analog/digital conversion on a real signal received by the dust sensor, and then solving an arithmetic mean value; and when the obtained arithmetic mean value is less than a certain preset value, judging that the transparent plates of the dust sensor need to be wiped. Thus the pollution degree of the transparent plates of the dust sensor is judged in real time, a wiping mechanism of the wiping system of the dust sensor is automatically started in time to wipe the transparent plates, therefore the accurate judgment of the dust sensor on dust quantity is effectively ensured, and the intelligent cleaning robot can normally work all the time.

A method is provided for reducing quadratic phase errors in synthetic aperture radar signals from a plurality of range lines where each range line includes a plurality of azimuth positions. The method includes receiving a plurality of slow-time samples representing radar signals for a plurality of azimuth positions for a plurality of range lines. A plurality of corrected samples and an initial quadratic phase error coefficient are identified based upon the slow-time samples. The corrected samples are processed according to a superresolution signal processing technique to thereby obtain a plurality of estimated Doppler frequencies for a plurality of point scatterers at each range line, after which a true signal for each range line is reconstructed based upon the plurality of estimated Doppler frequencies. A correction to the initial quadratic phase error coefficient is then obtained based upon the corrected samples, the true signals and the initial quadratic phase error coefficient.

An artificial neural network, ANN, and method of training the ANN for inversion of logging tool signals into well logs of formation parameters is disclosed. Properly selected synthetic models of earth formations are used to train the ANN. The models include Oklahoma and chirp type of formations. In each model parameter contrasts of from 10 to 1 to about 100 to 1 are included. Models including maximum and minimum parameter values spanning the operating range of the selected logging tool are included. Parameter contrasts at interfaces are limited to realistic values found in earth formations. The selected models are used to generate synthetic tool signals, which are then used as inputs to the ANN for training. When the ANN coefficients are properly adjusted to produce an output matching the original models, the ANN can be used for inversion of any real signals from the selected logging tool.

An error adjustment method of equalizing transmission characteristics of a signal processing circuitry is disclosed. In a first step, an original complex IQ signal is generated, on which error adjustment is performed. Then, the adjusted complex IQ signal is processed in the signal processing circuitry, thereby obtaining a processed real signal. The envelope of the real signal is detected and this real signal envelope and the original complex IQ signal are synchronized. The envelope of the original complex IQ signal is derived and the synchronized real signal envelope is compared with the synchronized original IQ signal envelope at two consecutive time instances. Finally, a processed complex IQ signal is obtained from the real signal envelope on the basis of the comparison result, which processed complex IQ signal is used in performing error adjustment.

The invention discloses an anti-spoofing-attack method and system applied to a satellite navigation system. The method comprises the following steps: S1) capturing and processing satellite signals, and obtaining code Doppler information and carrier wave Doppler information of the satellite signals; S2) carrying out consistency detection on the code Doppler information and the carrier wave Doppler information to obtain a consistency comparison result; and S3) judging whether the satellite signals are spoofing signals, sending alarm information if the satellite signals are spoofing signals, and sending current code phase position and carrier wave frequency information to a preset tracking loop if the satellite signals are not spoofing signals. The method and system in the invention not only can judge whether the spoofing signals exist in the received signals, but also can judge which signals are the spoofing signals and which signals are real signals, that is, the second layer can be reached; and the method and system have spoofing signal suppression function and also have strong anti-spoofing capability.

The invention provides a sonar moving target imaging method based on target echo Doppler characteristics, which comprises the following steps of: performing band-pass filtering on echo data of each basic element in a receiving basic array; performing band-pass filtering on each frequency point signal to acquire band-pass data of each frequency point; performing quadrature demodulation on the datasubjected to band-pass filtering of each frequency point to acquire an analytic signal form of a real signal; performing Chebyshev weighting and focusing operation on the echo data subjected to quadrature demodulation of each frequency point; acquiring image data of each frequency point in a polar coordinate system by fast Fourier transform (FFT) beam forming; and performing interpolation mergingon the image data subjected to FFT beam forming of each frequency point, and converting an image in the polar coordinate system into an image which accords with the visual habit of people in a rectangular coordinate system by sector conversion. By the FFT beam forming, the method can be implemented by an FFT algorithm in digital signal processing, and the requirement of system real-time imaging is met.

The invention discloses a method for identifying pipeline leakage, which comprises the following steps: aiming at two observation signals of adjacent sensors, using the signals as an input signal and a reference signal of a self-adapting filter respectively, and extracting a weight vector of the filter during convergence, wherein the weight vector is the optimal estimation of the correlation functions of the two observation signals; judging that a pipeline probably leaks when the weight vector of the filter during the convergence has a peak value, otherwise judging that the pipeline has no leakage; and when the judgment result is that the pipeline probably leaks, calculating the weight vector complexity value of the part beyond one neighborhood of the envelope peak value of the weight vector, and inputting the weight vector complexity value into a decision algorithm to finally determine whether the pipeline leaks really. The method has the following technical advantages: not only the noise-signal ratio of signals is improved, but also the correlated characteristics about leakage signals shared in the two signals are highlighted, and the decision algorithm is adopted to perform quantitative analysis on the complexity of the self-adapting filtering weight vector, eliminate noise interference and identify whether a signal source is a real signal source having the leakage.

For enabling determination on whether a sign of a Doppler frequency or a target angle is positive or negative even when only a real signal can be obtained as a received signal, the present invention provides a radar device including: an oscillator; a transmitting element; a distributor; receivers using the local wave to detect the received wave to generate a real received signal; a plurality of inter-channel phase correcting units; a spatial frequency information generating unit for converting a received signal string obtained by gathering a plurality of phase-corrected received signals into a signal in a spatial frequency domain; and a sign selecting unit for selecting a signal having a larger amplitude in a spatial frequency spectrum when two signals from a positive direction and a negative direction which are symmetrical with respect to a direction at approximately 0 degree.

A BPF outputs a real RF signal by suppressing a band out of an RF signal frequency band in a received signal. A local oscillator outputs a complex local signal with a predetermined frequency. A half-complex mixer performs frequency conversion by multiplying the real RF signal by a real part of the local signal, performs frequency conversion by multiplying the real RF signal by an imaginary part of the local signal, and outputs a complex signal separated by the predetermined frequency from a frequency of the real RF signal. A complex-coefficient SAW filter performs a convolution integral on an impulse response generated by an even function for a real part of the complex signal, performs a convolution integral on an impulse response generated by an odd function for an imaginary part of the complex signal, and outputs a real signal by suppressing one side of a positive or negative frequency.

A system and method for broadcasting decoy signals and an authentic signal in a location of interest are disclosed. A particular embodiment includes: initiating a local broadcast of decoy signals from a plurality of mobile devices in a location of interest, the local broadcast of decoy signals extending beyond the location of interest; initiating a local broadcast of an authentic signal from a first mobile device of the plurality of mobile devices in the location of interest; enabling the plurality of mobile devices to receive and retransmit the decoy signals and the authentic signal; and authorizing a second mobile device of the plurality of mobile devices and enabling the second mobile device to differentiate the decoy signals from the authentic signal.

The invention discloses a GNSS spoofing interference detection method based on a convolutional neural network. The GNSS spoofing interference detection method comprises the following steps that (1) inthe signal acquisition phase, the number N<peak>, greater than an acquisition threshold, of correlation peaks in a two-dimensional matrix A generated during signal acquisition is detected, if N<peak>is no less than 2, it is considered that a spoofing signal exists, if N<peak> is less than 2,the step two continues to be conducted; and (2) a detection matrix As is obtained by intercepting data inthe +/-2 chip area on pseudo code phase axes of the correlation peaks of the two-dimensional matrix A, after data preprocessing, the convolutional neural network conducts detection training and classification, and finally a detection result is obtained. The detection method has the good detection effect and high applicability, and the detection period is in the signal acquisition stage, and complexity is moderate; and the problem difficult to detect when the pseudo phase difference delta T between the spoofing signal and a real signal is within two chips can be solved.

The invention relates to an adaptive redundant lifting wavelet noise reduction analysis-based bearing failure recognition method, belonging to the technical field of failure recognition of a rolling bearing. The technical scheme is that the method comprises the following steps of: (1) performing adaptive redundant lifting wavelet transformation of a bearing vibration signal; (2) performing variable-size threshold noise reduction processing on a high-frequency detail signal obtained by each decomposition process; (3) performing complete reverse reconstruction on a low-frequency approximation signal obtained by final decomposition and a high-frequency detail signal subjected to wavelet threshold noise reduction; and (4) performing Hilbert demodulation processing on a reconstructed signal to obtain an envelope spectrogram of an initial vibration signal, extracting and recognizing a frequency component in the spectrogram, and judging that a bearing fails if frequency conversion or failure characteristic frequency and even corresponding frequency multiplication occurs. The adaptive redundant lifting wavelet noise reduction analysis-based bearing failure recognition method has the beneficial effects that a threshold can be flexibly selected according to the characteristic of change of noise in a wavelet region, so that noise can be filtered better, and meanwhile, the completeness of a real signal can also be guaranteed as much as possible.