31results about How to "Guaranteed filtering accuracy" patented technology

The invention discloses a digital filter capable of configuring a coefficient and an implementation method. A fitting factor which is obtained by fitting a filter coefficient according to a certain algorithm is stored in a memory, and a great quantity of storage spaces for storing the filter coefficient are saved under the condition of ensuring the filtering accuracy. The digital filter capable of configuring the coefficient comprises a fitting factor memory, a coefficient calculation module and the digital filter; the digital filter is connected to the fitting factor memory through the coefficient calculation module; the fitting factor memory is used for storing the fitting factor for fitting the filter coefficient through a fitting algorithm; the coefficient calculation module is used for reading corresponding fitting factor in the fitting factor memory to calculate and obtain the required filter coefficient according to the input control information, and digital filter uses the filter coefficient calculated by the coefficient calculation module to filter the input digital signal.

The invention discloses an atomic current sensor, which belongs to the field of electronics. The atomic current sensor comprises a light source control circuit, a light source, an atom absorption foam assembly and a sensor signal processing circuit, wherein the light source is controlled by using the light source control circuit; the atom absorption foam assembly is used for receiving an optical signal transmitted by the light source; and the sensor signal processing circuit interacts with the atom absorption foam assembly. Through the setting, the defect that an electromagnetic sensor applied in the fields of engineering detection of high-accuracy current detection, current metering detection and the like cannot well met requirements is overcome; and the atomic current sensor is simple in structure, has high measuring accuracy, and is suitable for popularizing and using.

The invention discloses a proportional control and normalized LMP filtering method under the CIM function, comprising the following steps: multiplying the input signal of the adaptive filter with the optimal weight vector of the filter, adding the noise signal, and obtaining the expected output Signal; multiply the input signal and the real-time weight vector of the filter to obtain the real-time output signal; make the difference between the expected output signal and the real-time output signal to obtain the signal error; design the cost function of the filtering algorithm according to the minimum mean square p-norm criterion; introduce Proportional step size control matrix, the weight update equation is obtained by the steepest descent method and normalized; the CIM function is introduced to optimize the proportional step size control matrix, so that each weight component can obtain a corresponding step size factor; the adaptive filter The weights are updated iteratively. The invention can ensure the filtering accuracy and convergence speed of the self-adaptive filtering method, even when the channel sparsity becomes smaller, it can still maintain better filtering accuracy and convergence speed.

The invention relates to a disturbing target filtering method of a radar target tracking system based on an alpha-beta filter. Compared with the prior art, the invention solves the defect that the filtering accuracy cannot be guaranteed when a radar tracks an unknown target. The method comprises the following steps: setting of a radar target tracking system; establishing of a virtual noise model;estimation calculation; filtering of a self-tuning alpha-beta filter. The method establishes a virtual noise model by using a method for fitting the virtual noise, and the system with parameter disturbance is transformed into a filtering problem with stable unknown parameters and known noise by using the virtual noise instead of disturbance and dynamic noise of the system itself. Therefore, a self-tuning alpha-beta filter is generated, which is used to filter the unknown targets effectively and ensure the filtering accuracy.

The asynchronous realization method of a distributed constrained edge-varying FIR graph filter according to the present invention, by introducing an advanced distributed constrained-edge-varying FIR graph filter, enables nodes to follow a random collection-calculation-broadcasting scheme. The distributed constrained edge-varying FIR graph filter is used for filtering operation to realize the graph signal denoising problem. The optimization goal is to minimize the error between the filtered signal and the node asynchronous communication output signal. The optimization problem is solved by genetic algorithm to get Coefficients of optimal distributed constrained edge-varying FIR graph filters. The beneficial effects of the present invention are as follows: the performance of the distributed graph filter can be improved at the expense of increasing the amount of computation, the communication energy consumption can be effectively saved, and the problem of signal denoising can be solved through the distributed constrained edge-varying FIR graph filter. , its denoising effect is better than that of other denoising image filters. Finally, Genetic Algorithm (GA) is used to solve the optimization problem to obtain the optimal graph filter coefficients.

The invention relates to a method for removing interference noise from moving object locating in a wireless sensor network (WSN), providing a prerequisite foundation to the design of a wave filter capable of accurately and quickly locating the actual position of a moving object in the environment that the wireless sensor network is interfered by noise, and according to the requirements of the wireless sensor network to the locating precision of the moving object, a UKF wave filtering algorithm is applied to partial particles in a UPF algorithm so as to obtain a better importance function. Foroccasions requiring high precision, more particles of the UKF wave filtering algorithm are applied, but for occasions requiring relatively low precision, fewer particles of the UKF wave filtering algorithm are applied, thereby providing the prerequisite foundation to the design of the wave filter capable of accurately and quickly locating the actual position of the moving object in the environment that the wireless sensor network is interfered by the noise.

The present invention provides a robust adaptive filtering and state estimation method based on Huber estimation. Firstly, an estimation value is calculated through estimating an upper bound of a covariance matrix of a one-step prediction dual-uncertainty system in an online way, only a time updating process is modified, at the same time a method of a linear matrix inequality is used to carry out adaptive parameter adjustment, and an adaptive traceless information filter for an uncertainty model is obtained. Then the matrix inversion theorem is applied and a Huber estimation method is used to modify a measurement update process, and a final estimation value is obtained. The precision of filtering and state estimation is high, and the stability is good. According to the robust adaptive filtering and state estimation method, a filtering and state estimation problem of a dual-uncertainty unmanned ship is solved, the advantages of an information filter structure are retained, the precision and stability of filtering and state estimation are improved, and the calculation is simple and the application is convenient.

The invention discloses a method for extracting characteristic peaks of ultraviolet Raman spectra with low signal-to-noise ratio, belonging to the field of spectrum detection and spectrum processing technology and signal processing. The invention collects ultraviolet Raman signals in real time, performs statistics on collected Raman signal data, and predicts the effective peak value of Raman signals. Each frame of Raman spectrum collected is processed, and for each frame of Raman spectrum, each frame of Raman spectrum is divided into various regions through the obtained effective trough, and the properties of each segmented region are judged separately . For each noise region, let each point be equal to the minimum value of the region, and then merge the Raman signal region and the processed noise region. Afterwards, the processed N+1 frame spectra are spliced ​​into a 2D image along the time axis, and the 2D image is filtered through an iterative bilateral filtering method. After filtering, the N+1 spectra are superimposed and normalized along the time axis. Obtain clean Raman characteristic peak spectral images.

The invention discloses a filtering method of a linear random system. The filtering method comprises the steps of adding a noise superposing item to the linear random system, and obtaining a noise superposed linear random system; performing observation value expression construction processing according to the noise superposed linear random system, and obtaining an observation value expression; andaccording to an optimal filtering method, performing filtering processing through using the noise superposed linear random system and the observation value expression as parameters, thereby obtaininga filtering result. Through adding the noise superposing item into to the linear random system, the linear random system bears the system noise interference at a previous time point and the system noise interference at the current time point, thereby relatively completely simulating a noise interference environment in an actual condition, further improving subsequent filtering precision and realizing higher filtering processing accuracy. The invention further discloses a linear random system filtering device, another filtering device and a computer-readable storage system, wherein the beneficial effects described above are achieved.

The invention provides a TS-InSAR atmospheric phase filtering method based on blocking strategy. The method comprises the following steps: dividing the original SAR image data into equal data blocks and gathering the information of permanent scattering points; with the data blocks as a center to select a central data block group and based on the established filtering parameters and the information of permanent scattering points, calculating the central filtering value of the central data block group and the filtering value surrounding the central data block group; and based on the central filtering value of the central data block group and the filtering value surrounding the central data block group, obtaining the filtering value of the permanent scattering points. The present invention eliminates the need to repeatedly calculate the filter value of each permanent scatter point, greatly improving the filtering efficiency. The combination of a precisely filtering method and approximately filtering method ensures high precision while increasing the speed considerably. The method can be adaptive to different filtering radiuses and different data types.

The invention discloses a wireless transmission device based on software radio filtering and a method thereof, belonging to the technical field of wireless communication. The device comprises a radio frequency transmitter, a radio frequency receiver, a transmission digital signal processing module and a receiving digital signal processing module, wherein the transmission digital signal processingmodule is connected with the radio frequency transmitter to transmit a digital signal; the radio frequency transmitter is wirelessly connected with the radio frequency receiver to transmit a wirelessanalogue signal; and the radio frequency receiver is connected with the receiving digital signal processing module to transmit an analogue signal. By adopting a filtering pre-processing method based on EMD and considering the characteristic of the wireless signal, the invention filters noises spreading all over frequency bands in the signal by means of EMD after the signal is received by a receiving antenna so as to ensure the filtering accuracy and the reliability of the wireless signal transmission with excellent effect. The invention can be applied to the filtering scheme of industry wireless communication and lay the foundation for wide application of the industry wireless communication.

A channel estimation method and device, a computer-readable storage medium, and a terminal, wherein the channel estimation method includes: performing preliminary channel estimation using pilots in the frequency domain to obtain multiple initial channel estimation values; using a filter bank to select The M initial channel estimation values ​​are filtered to obtain multiple filtering results, the filter bank includes multiple filters with various passband widths, and M is the number of taps of the filter in the filter bank; Among the plurality of filtering results, the filtering result with the smallest error value from the M initial channel estimation values ​​is selected as the channel estimation value. The accuracy and scope of application of channel estimation can be improved through the technical scheme of the invention.