320 results about "Process noise" patented technology

An auxiliary dust collection system can be interposed between a sander or other dust producing tool and a vacuum source, e.g., shop vacuum. This auxiliary system has a cyclonic separator connected by a flexible hose to the tool and by another hose to the vacuum source. The cone of the separator is mounted onto the lid of a drum into which the dust precipitates. For a tool that has its own blower, the vacuum source can be omitted, and the air leaving the outlet duct of the separator can be filtered and returned to the ambient. A drop in silencer formed of a sleeve or tube of acoustic foam can be positioned into the inlet side of a filter cartridge following a cyclonic separator. The silencer absorbs a significant fraction of the process noise.

The invention discloses a self-adaptive tracking loop, which comprises an unscented Kalman filter (UKF), an observation noise variance matrix detection module, a fuzzy inference system, an unscented transformation (UT) scale factor regulation module, a state compensator, a carrier wave numerical controlled oscillator (NCO), scale factors, a code NCO, an integration and zero-clearing module, a code loop phase discriminator and a second order code loop filter, and additionally discloses an implementation method for the self-adaptive tracking loop. The implementation method comprises a step 1 ofsignal correlation, integration and zero clearing; a step 2 of code phase tracking; a step 3 of UKF modeling; a step 4 of observation noise variance matrix estimation; a step 5 of process noise variance matrix estimation; a step 6 of UT scale factor regulation; a step 7 of state estimation deviation compensation; and a step 8 of assistance of the carrier wave NCO in the code NCO. According to theself-adaptive tracking loop, the UKF, the observation noise variance matrix detection module and the fuzzy inference system are designed in the carrier tracking loop, so not only can a contradiction between thermal noise vibration in the tracking loop and a dynamic stress error be solved, but a process noise variance matrix and an observation noise variance matrix can be regulated in a self-adaptive manner according to changes of the external environment, and thereby the self-adaptive ability of the tracking loop under complex changeable environments of high dynamic, strong interference, and the like is effectively improved.

The invention discloses a method for estimating junction temperature on line by an IGBT (Insulated Gate Bipolar Transistor) power module. The method comprises the following steps: estimating the junction temperature by using a thermo-sensitive electrical parameter method; establishing an extended state space thermal model; and applying a Kalman filter in junction temperature estimation. The thermosensitive electrical parameter method can estimate the junction temperature of an IGBT power module in real time, an IGBT conduction voltage drop VCE (ON) is selected as a thermosensitive electrical parameter, and a VCE (ON) online measurement circuit is provided. On the basis of a Foster thermal network model, the influence of diode coupling is considered, and an extended state space thermal model comprising self-heating and coupling heat is provided; And taking the power loss of the diode and the IGBT and the junction temperature estimation value obtained by using the thermosensitive electrical parameter method as the input of the Kalman filter, and considering the measurement noise and the process noise, thereby obtaining the optimal junction temperature estimation value. According to the method, electrical insulation is achieved, measurement is carried out without changing a control strategy of the power converter, noise is reduced, the intermittent influence of voltage measurementis eliminated, and the junction temperature measurement precision is improved.

An accessory device for a ballistic thrower / launcher that can be handgun or a gun or other object throwing or launching device that is meant to improve the quality of the action, the comfort and safety of the operator. It is made of accessory devices that stabilize the operation of the throwing device aligning the recoil with the projectile trajectory making the process reproducible, predictable and controllable. It adds environment monitoring electronics, cameras and actuators, for accurately launching after aiming, considering all the major process perturbations, as movements, wind, humidity, atmospheric pressure, target movement, shooting post movement, etc. The device adds other features of safety for the operator, as stealth action, dimming process noise, recoil shock, flames and heat signature being suitable for remote operation.

Provided is a capacitive touch sensor which includes a flat panel display for displaying an image and a touch sensor panel positioned on the flat panel display or embedded in the flat panel display. The capacitive touch sensor may include: a driving clock generator configured to generate time-periodic output signals with respect to a plurality of times, and apply the generated time-periodic output signals to the touch sensor panel and a receiver circuit unit; a driver configured to generate a driving signal of the touch sensor panel using a part of the output signals of the driving clock generator; and the receiver circuit unit configured to process noise contained in a signal received from the touch sensor panel, using the output signals.

The invention relates to a self-adaptive fault-tolerant cubature Kalman filtering method applied to target tracking. The present invention generally includes three parts of content. Wherein the firstpart performs system modeling according to an actual moving target; Secondly, estimating noise statistical characteristics according to an improved adaptive filtering method; And a third part, detecting a fault according to a chi-square test, and carrying out weighting processing on the information part during state estimation according to a detection result. The method not only can dynamically estimate the process noise covariance and the measurement noise covariance at the same time, but also can cope with the condition that data measured by the radar break down, and achieves the effective tracking of a target.

The invention provides an SOC (state of charge) estimation method for controlling equivalent charging and discharging of a lithium battery. The SOC estimation method includes: establishing a first-order RC (resistor and capacitor) equivalent circuit model of a single lithium battery, and determining a state equation and an observation equation of a lithium battery system; determining a Kalman filtering discrete state space model, a state parameter variable and an observation parameter variable; updating an predicted value of the state parameter variable and a covariance matrix of measuring errors, and acquiring an innovation sequence according to an observed voltage value at the end of the lithium battery; introducing a self-adaptive fading factor to track and correct a predicted covariance matrix of the lithium battery system; calculating a Kalman filtering gain matrix of the discrete state space model, and updating the optimal estimated value and an error covariance matrix value at the present moment; acquiring a statistical property of process noise; acquiring an SOC estimation value at the present moment, and putting the parameters of the present moment in recursive iteration calculation of strong-tracking self-adaptive Kalman filtering for the next moment. By the aid of the SOC estimation method, real-time and precise estimation of SOC of the lithium battery is realized.

The invention provides a navigation decoy system and method for a coexistence unmanned aerial vehicle. The decoy system comprises a satellite search system, a cheat signal generation control system and a signal transmission system. The satellite search system is used for receiving and parsing a true satellite signal, and parsed result data is transmitted to the cheat signal generation control system; the cheat signal generation control system is used for calculating related parameters and generating a cheat signal; the signal transmission system sends the cheat signal generated by the cheat signal generation control system to a target unmanned aerial vehicle, and a receiver of the target unmanned aerial vehicle captures and tracks the cheat signal and the true satellite signal at the sametime; the cheat signal generation control system increases the power of the cheat signal to remove the true signal and controls a tracking loop of the target unmanned aerial vehicle. According to thenavigation decoy system and method, a synchronous false satellite is generated and coexists in the target receiver with a sky satellite, the power of the cheat signal is gradually increased after coexistence, the processed noise basis of the receiver is increased, and the output signal-to-noise ratio of the true signal in a correlator of the receiver is lowered; by relying on the power advantage of the cheat signal, the true signal is gradually removed out of the tracking loop, then the tracking loop is controlled, and cheat for the flight direction and speed of the black-flight unmanned aerial vehicle is achieved.

The present invention is concerned with the estimation of health parameters p(k) representing symptoms of a slowly degrading system, in particular industrial gas turbines. According to the invention, an estimation of a true health or independent parameter vector at time step k uses the estimation of the true health or parameter vector at a previous time step k−1 as a starting value for the production of a predicted health parameter vector at time step k. Based on the latter and a set of measured values of input variables of an extended model of the system, a prediction of output variables of the model is produced. This predicted model output is compared with measured values of the output variables to yield an error. From this error, a health parameter estimator in turn produces a health parameter estimate as a revision of the predicted health parameters. Preferably, the estimation of a true health or independent parameter vector at time step k includes a generalised process noise representing stochastic uncertainty and / or a-priori knowledge of an evolution of the health parameters.

An auxiliary dust collection system can be interposed between a sander or other dust producing tool and a vacuum source, e.g., shop vacuum. A cyclonic separator is connected by a flexible hose to the tool and by another hose to the vacuum source. The cone of the separator is mounted onto the lid of a drum into which the dust precipitates. For a tool that has its own blower, the vacuum source can be omitted, and the air leaving the outlet duct of the separator can be filtered and returned to the ambient. A drop in silencer formed of a sleeve or tube of acoustic foam can be positioned into the inlet side of a filter cartridge following a cyclonic separator. The silencer absorbs a significant fraction of the process noise. The acoustic foam can have a textured surface on the sound-facing side.

The invention provides a depth map fusion method and a depth map fusion device. The depth map fusion method comprises the following steps of: extracting depth maps from scenes at different visual angles according to scene information acquired by a plurality of cameras; clustering the depth maps extracted from the different visual angles; establishing a deletion matrix according to the clustered information; recovering the deletion matrix to obtain a complete low-rank matrix; selecting a first dimensional subspace from the complete low-rank matrix according to an elastic network algorithm; andreconstructing a three-dimensional model according to the first dimensional subspace. The depth map fusion method has the advantages of effectively processing noise and having high accuracy for processing standard data simultaneously.

The invention provides a lithium battery SOC estimation algorithm based on dual adaptive unscented Kalman filter. The algorithm utilizes the advantages of a Kalman filter to track the accurate state value of SOC and is free of cumulative errors caused by a traditional time integration method. In particular, through the use of an adaptive unscented Kalman filter, the SOC value of a lithium battery can be estimated in real time; a covariance matrix of process noise and measurement noise can be estimated on-line; this avoids the filter estimation performance degradation of a traditional Kalman filter due to the only assumption that there exists Gaussian white noise in an estimation process and even the problem that filter divergence deviates from the true value, etc. The algorithm provided by the invention conducts filter calculations and utilizes a noise statistic estimator to perform on-line correction to the statistics of the unknown or inaccurate noise in real time so as to realize on-line estimation of a lithium battery SOC and to improve the precision and accuracy of SOC estimation. The convergence speed is greatly enhanced under the condition with erroneous initial SOC.

The invention provides a voice enhancing method, which comprises the following steps of: providing a microphone and a voice signal processing chip integrated in the microphone, wherein the microphone is used for receiving external signals, and the voice signal processing chip is used for performing voice enhancing processing; and transforming frequency domain signals obtained by processing noise voice signals to a time domain, and performing deemphasis processing to obtain output signals. The method can realize the microphone directivity, and enhances the capacity of processing the voice signals.

Null processing noise subtraction is performed per sub-band and time frame for acoustic signals received from multiple microphones. The acoustic signals may include a primary acoustic signal and one or more additional acoustic signals. A noise component signal may be determined for each additional acoustic signal in each sub-band of signals received by N microphones by subtracting a desired signal component within every other acoustic signal weighted by a complex-valued coefficient σ from the secondary acoustic signal. The noise component signals, each weighted by a corresponding complex-valued coefficient α, may then be subtracted from the primary acoustic signal resulting in an estimate of a target signal (i.e., a noise subtracted signal).

This invention relates to methods and devices for time and frequency synchronization, especially over packet networks using, for example, the IEEE 1588 Precision Time Protocol (PTP). Timing protocol messages are exposed to artifacts in the network such as packet delay variations (PDV) or packet losses. Embodiments of the invention provide a recursive least squares mechanism for clock offset and skew estimation. A major potential advantage of such estimation is that it does not require knowledge of the statistics of the measurement noise and process noise. An implementation using a digital phase locked loop based on direct digital synthesis to provide both time and frequency signals for use at the slave (time client) is also provided.

A method and apparatus for estimating and compensating for a broad class of non-Gaussian sensor and process noise. In one example, a coded filter combines a dynamic state estimator (for example, a Kalman filter) and a non-linear estimator to provide approximations of the non-Gaussian process and sensor noise associated with a dynamic system. These approximations are used by the dynamic state estimator to correct sensor measurements or to alter the dynamic model governing evolution of the system state. Examples of coded filters leverage compressive sensing techniques in combination with error models based on concepts of compressibility and the application of efficient convex optimization processes.

Methods and apparatus for online estimation of battery model parameters for determining a State-of-Charge (SoC) and a State-of-Health (SoH) of a battery are provided. A mathematical approach using voltage, current, and temperature samples at programmable intervals to estimate RC battery model parameters is utilized, reducing computational requirements to enable real-time estimation of the SoC in an online environment. The SoC estimation utilizes an optimal estimator with an Extended Kalman Filter (EKF) to reduce sensitivity to process noise and measurement errors. After a discharge or charge operation, the SoH can also be estimated and updated as necessary.

The invention relates to a voice denoising method based on computational auditory scene analysis and countermeasure network model generation. The method comprises the following steps: S1, processing noise-containing noises based on a generator generating a countermeasure network and a discriminator, thus obtaining an intermediate result; and S2, processing the intermediate result based on the computational auditory scene analysis method, thus obtaining a final result. With the method provided by the invention, part of noises in the voice signals obtained under the complicated channel background environment can be removed, and that no distortion occurs on the voice part can be well kept.

An implementation of a system and method for using inertial sensor data to improve mobile station positioning is provided. Many mobile devices include an inertial sensor. These inertia measurements typically produce low resolution inertial measurements, which may be used to generate an uncertainty value and / or to select a positioning filter model. In some embodiments, this uncertainty value is used as a process noise input signal into a Kalman filter or similar filter. In some embodiments, one position estimate is selected from multiple navigation position filter models operate concurrently, each computing a separate position estimate. In these embodiments, a position estimate is selected based on either the uncertainty value or based on another characteristic of the inertia measurements.

The invention discloses a quaternion-based attitude resolving method for an extended Kalman filter algorithm. The method comprises the following steps: acquiring multisensor data of a vector in a fixed coordinate system; filtering data acquired by an accelerometer and a magnetometer, and subjecting the data acquired by the two sensors to normalization processing; constructing a state equation of avector system according to a quaternion differential equation and an attitude matrix, and determining a process noise variance matrix of the system; constructing a systematic observation model by using a rapid Gauss-Newton method, and determining a system measured noise variance matrix; constructing a Kalman filtering recurrence equation according to the constructed system state equation and theobservation model; resolving three attitude angles of the vector by using an optimal quaternion obtained through recurrence. According to the method, the computing capacity can be greatly simplified,and the existing problem that parameters are unclear in computing is solved.

The invention discloses a target tracking method of a passive multi-sensor based on layered particle filtering. A sub-state including an azimuth angle, a change ratio of the azimuth angle, a change ratio of a logarithm radial distance and auxiliary parameters and a sub-state Psi including the logarithm radial distance are constructed to realize a structure of hierarchical filtering through rewriting a system equation of a logarithm polar coordinate and adding the auxiliary parameters indicative of process noise intensity and radial distance ratio, wherein a first layer updates the auxiliary parameters in a second layer by means of sequential importance sampling method according to observation information of various sensors; Psi is iterated and updated; and the auxiliary parameters are combined to obtain estimation of the target state; finally a fusion output result of the target state is obtained according to an optimal information fusion method. Values of the auxiliary parameters can be estimated in real time by using a method of the layered particle filtering, and errors introduced by a maximum value of the noise intensity in the use process of the filtering is avoided, such that the problem of the target tracking can be effectively solved under the conditions of unknown process noise intensity and unmeasured distance.

The invention discloses a method and system for dynamically suppressing power line impulse noise. A power line impulse input code stream is modulated, and part of peak values of each OFDM symbol that are obtained are quantized and coded, and are then input to a power line channel together with the OFDM symbols; a receiving end receives signals on a power line, the abovementioned part of peak values are recovered from coded signals, an average value of the peak value information is calculated, a received OFDM symbol sampling value is compared with the average value, thereby judging the magnitude of noise; three different noise suppression methods of deep amplitude limiting, amplitude limiting and blanking are used to process each OFDM symbol according to difference of the magnitude of noise; and blanking and amplitude limiting thresholds of the three noise suppression methods are determined by using a threshold value optimization method, and data after processing is completed are sent to an OFDM demodulation module. The method for dynamically suppressing the power line impulse noise adopts different noise suppression methods to process noise according to different situations of the magnitude of impulse noise. The deep amplitude limiting method keeps the basic features of signals; the blanking method performs zero setting on detected impulse noise, and immediately eliminates interference among the signals without affecting system performance; and the amplitude limiting mode is easy to realize.

The invention provides a generator dynamic estimation method considering model parameter uncertainty. According to the method, a generator dynamic state estimation model is established, wherein a classic model of a generator is established, and a dynamic state estimation equation and a measurement equation of the generator are constructed; error analysis is performed, wherein an error variance matrix of measured values and process noise are considered; and adaptive robust extended Kalman filtering dynamic estimation is performed, wherein adaptive robust extended Kalman filtering is adopted toperform dynamic estimation on a power angle and an electric angle of the generator in an electromechanical transient process according to a generator state space model. Through the method, an estimation error upper limit brought by system parameter uncertainty can be effectively defined, and by the adoption of the adaptive technology to perform adaptive estimation on the parameters, the problem that the error upper limit is difficult to select through traditional robust extended Kalman filtering is avoided. Therefore, compared with existing methods, the method has higher robustness and higherestimation precision.

The invention discloses an OCT (Optical Coherence Tomography) image denoising method based on dense connection and a generative adversarial network, which belongs to the technical field of image restoration, and adopts a multi-frame registration mode to synthesize a reference image according to the characteristics of noise randomness, so that the network can learn a mapping relationship between anoise image and the reference image; the noise synthesis step can effectively expand the diversity of speckle noise and synthesize new sample data; dense fusion is carried out by using multi-scale features of the network, and repeated utilization and transmission of effective features are enhanced by using fewer parameters; the overall perception quality of the image is ensured by adopting an adversarial generative network mode; the trained generative model can directly process noise OCT images with any resolution, has high speed and performance, and has high use value in clinic.

The invention discloses a two-stage separation fusion attitude and heading estimation method, which comprises the following steps: establishing a Kalman filter state equation and a measuring equation of a system, wherein xk and yk denote a state vector and an observation vector of the system respectively, wk and vk are state equation process noise and observation equation measurement noise respectively, k denotes the timing of the calculation; f is the transfer function between state vectors at adjacent moments; calculating the state vector obtained from the Kalman filter state equation, and obtaining a pitch angle theta and a roll angle phi by calculating according to the figure. The two-stage separation calculation is carried out for an attitude angle and a heading angle, the use in a non-linear filtering method such as extended Kalman filter and unscented Kalman filter methods can be avoided by the established linear filter equation, and the calculation complexity of the system can be greatly reduced. Meanwhile, the first-stage Kalman filter is responsible for calculating the attitude angle using a gyroscope and an accelerometer, and a magnetic sensor does not participate in the first-stage filtering, so that the effect of the interference with the magnetic sensor on the attitude angle estimation is eliminated.

The invention provides a UUV (unmanned underwater vehicle) aided navigation method based on current profile. The method comprises the following steps: firstly setting up a Kalman filter model of current profile data, secondly determining the observation noise variance R and process noise variance Q in a Kalman equation according to variations of the environment and the UUV own velocity and finally setting up a UUV velocity-current profile relation database, utilizing the relation database and the current profile information measured by an ADCP (acoustic Doppler current profile) to reckon the UUV velocity at the time of DVL (Doppler velocity log) failure and further obtaining the navigation position of the UUV by deadreckoning. The method has the following beneficial effects: when the UUV performs a task under water, once the sonar data of the DVL have failure, the UUV velocity can be reckoned by using the current profile information measured by the ADCP, so that the UUV can continue performing the ocean exploration task in the complex ocean environments such as great depth, thus improving the environmental adaptation capability of the UUV.

The invention discloses a method for performing dentition segmentation on a cone beam CT image (CBCT). The method for performing dentition segmentation on a cone beam CT image comprises steps of defining an image structure according to an interest body image area in the cone beam CT image, obtaining a complete dentition through segmenting the CBCT image on the basis of a semi-supervised random walk algorithm and a soft constraint which is defined and registered by a three-dimensional deformable model, using the three-dimensional deformable model to introduce a soft constraint of a body image for processing noise in body image segmentation based on semi-supervised mark diffusion, adopting an iteration correction method to perform iteration solving problems on mark diffusion under the soft constrain and fitting on a surface voxel set by the three-dimensional model. The method for performing dentition segmentation on the cone beam CT image can effectively eliminate a segmentation error, improves dentition segmentation obtained through single time mark diffusion, improves segmentation accuracy and meets an accuracy requirement for clinic stomatology.