4677results about How to "Improve estimation accuracy" patented technology

An improved apparatus and methods of posture and physical activity monitoring. The apparatus is physically mountable to or associated with an object or person, includes a multi-axis accelerometer, and derives measurements of posture and of acceleration. Methods are disclosed which provide improved estimations of posture, acceleration, energy expenditure, movement characteristics and physical activity, detect the influence of externally-caused motion, and permit automatic calibration of the apparatus in the field.

Methods, apparatuses, and systems directed to a wireless node location mechanism that uses a signal strength weighting metric to improve the accuracy of estimating the location of a wireless node based on signals detected among a plurality of radio transceivers. In certain implementations, the wireless node location mechanism further incorporates a differential signal strength metric to reduce the errors caused by variations in wireless node transmit power, errors in signal strength detection, and / or direction-dependent path loss. As opposed to using the absolute signal strength or power of an RF signal transmitted by a wireless node, implementations of the present invention compare the differences between signal strength values detected at various pairs of radio receivers to corresponding differences characterized in a model of the RF environment. One implementation of the invention searches for the locations in the model between each pair of radio receivers where their signal strength is different by an observed amount.

An improved apparatus and methods of posture and physical activity monitoring. The apparatus is physically mountable to or associated with an object or person, includes a multi-axis accelerometer, and derives measurements of posture and of acceleration. Methods are disclosed which provide improved estimations of posture, acceleration, energy expenditure, movement characteristics and physical activity, detect the influence of externally-caused motion, and permit automatic calibration of the apparatus in the field.

An operation determination processing section of a center extracts words included in the utterance of a driver and an operator, reads an attribute associated with each word from a synonym and related word in which an attribute is stored so as to be associated with each word, reads a domain of a candidate or the like for the task associated with the attribute from the synonym and related word in which domains of a candidate for a task associated with the read attribute or domains of a task to be actually performed are stored, totals the domains read for each word for words included in the utterance of the driver or the like, and estimates those related to a domain with a highest total score as the candidate for the task and the task to be actually performed. In this manner, it is possible to estimate the task with high accuracy.

A network performance (e.g., latency and bandwidth) measurement infrastructure for large scale networks based on self-organized probing groups of devices. Each group of devices has a lead device that measures network characteristics, and then shares the measurement information with other devices. This grouping method reduces the amount of network bandwidth needed for adequate measurements, while still providing necessary information to individual devices. The system utilizes a novel multicast-based algorithm that is adopted for both intra-group and inter-group performance measurement. The measurement groups (MeGroups) are dynamic and self-forming, and use a set of heuristic algorithms to optimize the dynamic groupings.

A blood pressure monitoring apparatus which continuously estimates and monitors the blood pressure by using the pulse wave propagation time can accurately estimate the blood pressure. While an estimated blood pressure is continuously calculated by using the pulse wave propagation time, the correlation between the pulse wave propagation time and the interval between feature points contained in two consecutive heart beat waveforms of an electrocardiogram is monitored. If the correlation is reversed, the blood pressure is actually measured, and the estimated blood pressure is corrected on the basis of the difference between the estimated blood pressure and actually measured blood pressure.

The present disclosure relates to systems and methods for improving the accuracy of expected error estimations in hybrid cellular and WLAN location determination. In some embodiments, the method can include providing a WLAN based location estimate and an expected error estimate for the WLAN based location estimate, providing a cellular based location estimate and an expected error estimate for the cellular based location estimate, and determining the expected error of the location determination by evaluating the consistency of the cellular based location estimate to the WLAN based location estimate. In some embodiments, the location estimate with the lower expected error can be selected as the location determination of the WLAN and cellular enabled device. In some embodiments, the consistency of the estimates can include the distance between the cellular based location estimate and the WLAN based location estimate.

To achieve an improved overview on service charges for a subscriber to a digital cellular communication network it is proposed to provide a mobile station with a charging indicating unit (6) adapted to receive charging information as unstructured supplementary service data messages (USSD) via the unstructured supplementary service data dialog. Therefore, it is possible to provide charging information without any impact on the hardware of the mobile station (MS). Further, as more detailed information on the kind of service and on the amount of data transferred is available a detailed estimate on the actual cost may be displayed to the user of the mobile station.

Transducers of different distributions detect the existence of targets of environment first and a test information composition system mixes the results detected by transducers to follow up the state and pick-up the character of the target. The state information composition system and the character dinformation composition system composite the traced states and identification results of character vector separately by each transducer to get relative accurate state parameter and identified results and information composition makes the entire systematic composition to provide favorable decision for next step, to increase systematic detecting probability, estimated accuracy and identified probability and more resonable algorithm.

A path planning unit plans a travel path to a destination based on an estimated current travel position and outputs a travel command to a travel control unit to perform travel control so as to follow the travel path. A travel position prediction unit accumulates a travel distance, which is detected by a wheel turning-angle sensor, to the estimated current travel position so as to predict the current travel position. A predictive image generating unit generates a plurality of predictive edge images which are composed of edge information and captured when a camera is virtually disposed at the predicted current travel position and candidate positions in the vicinity of it based on layout information of the environment, and an edge image generating unit generates an actual edge image from the actual image captured by the camera. A position estimation unit compares the edge image with the plurality of predictive edge images, estimates the candidate position of the predictive edge image at which the degree of similarity is the maximum, and updates the travel position of the path planning unit and the travel position prediction unit.

In order to locate and display the source of a sound such as a noise at a factory or the like accurately even when it is outside, a pair of microphones (M1, M3) and another pair of microphones (M2, M4) are disposed on the X axis and Y axis with a distance L therebetween, respectively, the direction of the sound source is estimated from a difference between sound arrival times to the microphones (M1, M3) and a difference between sound arrival times to the microphones (M2, M4), an image around the estimated location of the sound source is picked up by a camera, and the above estimated location of the sound source is displayed on the above image displayed on the display of a personal computer.

The invention discloses a gaze estimation method. The gaze estimation method comprises the following steps: finding out calibration error by aligning; then estimating the distance between a face plane and a screen and establishing a three-dimensional model to obtain optical axis information of eyeballs by offset correction of the head and rotary correction of the head; and finally, obtaining the position of a fixation point. According to the gaze estimation method, only a camera is used and no auxiliary equipment is needed; the aim of furthering increasing the estimation precision is achieved by using a correction link by a user; in addition, due to the utilization of estimation of the distance between the face plane and the screen and the offset and rotation correction of the head, limiting conditions are reduced as much as possible, a comfortable use environment for a user is provided and the gaze estimation method has better precision and adaptability of the head motion; and on the basis of an eyeball of a human eye, the gaze estimation method based on a three-dimensional model is established so as to achieve the aim of increasing the estimation precision. According to the gaze estimation method, extra auxiliary equipment is reduced, the adaptability to the head motion is improved, and the better precision for sight light estimation is obtained.

The invention is a charge state evaluation method and system of a power lithium ion battery. According to the method, step one is to establish a circuit model of an equivalent battery. Charging and discharging and standing experiments are performed on the battery, and timing sampling is performed so that a voltage time curve is obtained. Model parameters are identified via a formula so that a non-linear relation between an open-circuit voltage OCV and an SoC is obtained. Step two is to obtain an optical estimation value of the SoC by matrixes of state prediction, prediction error variance, filtering gain, state estimation, estimation error variance, etc., according to Kalman algorithm. According to the system, an analog / digital converter, a program storage device, a programmable storage device, a timer and a displayer are respectively connected with a microprocessor. A current sensor and a voltage sensor are respectively connected in a circuit formed by connecting the battery to be tested and a load, and outputs of the current sensor and the voltage sensor are accessed into the analog / digital converter. The programmable storage device stores battery model parameters obtained by the experiments. The program storage device stores estimation program of the method. Estimation precision of the SoC can reach 1%, and the charge state evaluation method and system is more stable; besides, the system provides estimation values of the SoC in real time.

The invention discloses a gaze estimation method for a head-mounted device based on iris and pupil. The method is characterized by utilizing a single camera, a single infrared light source and centre calibration points in four equal regions of a screen, extracting eye movement two-dimensional center features and carrying out three-dimensional space modeling on iris and pupil, establishing a three-dimensional gaze direction vector, and with gaze direction angle information being combined, estimating human eye gaze point position. Features of the head-mounted device are taken into full consideration; gaze point estimation precision under the head-mounted device is ensured, and meanwhile, complexity of the whole system structure and calibration process is greatly reduced; and the method is a high-precision and low-complexity solution method for eye-gaze tracking under the head-mounted device.

A wireless localization technology using efficient multilateration in a wireless sensor network is disclosed. After calculating estimated distances from each of at least three reference nodes to a blind node using received signal strength of wireless signals that the at least three reference nodes received from the blind node, the estimated location of the blind node is obtained through multilateration using the calculated estimated distances. To correct error in the estimated location, the estimated distances are used, and the error correction direction and error correction distance for the estimated location are calculated by applying a largest weight to the reference node closest to the estimated location. The error of the estimated location is corrected by move the estimated location of the blind node by the calculated error correction direction and error correction distance. Calculation for the error correction is very simple and fast.

An object is tracked among a plurality of image frames. In an initial frame an operator selects an object. The object is distinguished from the remaining background portion of the image to yield a background and a foreground. A model of the background is used and updated in subsequent frames. A model of the foreground is used and updated in the subsequent frames. Pixels in subsequent frames are classified as belonging to the background or the foreground. In subsequent frames, decisions are made, including: which pixels do not belong to the background; which pixels in the foreground are to be updated; which pixels in the background were observed incorrectly in the current frame; and which background pixels are being observed for the first time. In addition, mask filtering is performed to correct errors, eliminate small islands and maintain spatial and temporal coherency of a foreground mask.

The invention discloses an automotive exhaust emission data fusion system. The automotive exhaust emission data fusion system comprises a roadside air pollutant concentration estimation module, a roadside air pollutant concentration prediction module, a city global atmospheric environment prediction module, an automotive exhaust emission factor estimation module and an automotive exhaust emission feather analysis module, wherein the five modules are used for respectively realizing different data analysis functions, and the different functions can be realized by virtue of the different modules; the modules can be independently used, or two or more modules can be combined for use, so as to realize the storage, analysis and fusion of automotive exhaust telemetering data, automotive attributes, driving working stations, detection time and meteorological condition data; and by combining with a vehicle-mounted diagnosis system database, a portable emission test system database, a vehicle inspection station offline database, a traffic information database and a geographic information database, automotive exhaust telemetering data is analyzed, and the highest discriminatory key indexes and statistical data are acquired, so that effective supports are provided for the formulation of relevant decisions of government departments.

A light source estimation method of this invention estimates from the sensor response the color characteristics of an unknown light source of an image-pickup scene, in order to improve white balance adjustment and other aspects of the quality of color reproduction; a projection conversion portion 6 projects sensor response values 5 into an image distribution 9 in an evaluation space not dependent on the image-pickup light source 2 using parameters obtained by operations which can be calorimetrically approximated from spectral sensitivity characteristics of image-pickup unit 4, which are known, and from spectral characteristics of an assumed test light source 1; an evaluation portion 10 evaluates the correctness of a plurality of the test light sources 1 based on the distribution state of sample values of the projected scene; and accordingly, the correct image-pickup light source 2 is estimated.

The invention relates to a method for estimating attitude parameters of automatic landing of an unmanned air vehicle based on visual information, which comprises the following steps: 1) processing and calculating the motion vector and estimating the expansion center on the basis of time for monocular visual information and estimating the pitch angle according to a geometrical vanishing point model on the assumption that the unmanned air vehicle slides down along a straight line; 2) forming a sparse disparity map based on matching of characteristic points by utilization of binocular stereoscopic visual information, further estimating the depth information of a characteristic point from a UAV to the ground, and acquiring the height of the UAV relative to the ground by combination of the parameters of the pitch angle and conversion from the coordinate of a camera to the world coordinate; and 3) establishing a UAV motion model, and further improving the estimation precision of the height parameter of the UAV on the basis of Kalman filtering. The invention provides the method for estimating the attitude parameters of automatic landing of the unmanned air vehicle based on the visual information and effectively improving the reliability.

An automatic system for temporal alignment between a music audio signal and lyrics is provided. The automatic system can prevent accuracy for temporal alignment from being lowered due to the influence of non-vocal sections. Alignment means of the system is provided with a phone model for singing voice that estimates phonemes corresponding to temporal-alignment features or features available for temporal alignment. The alignment means receives temporal-alignment features outputted from temporal-alignment feature extraction means, information on the vocal and non-vocal sections outputted from vocal section estimation means, and a phoneme network, and performs an alignment operation on condition that no phoneme exists at least in non-vocal sections.

A system is provided that is configured to be transported, carried or worn by a user, such as a portable personal training device or sports watch. The system comprises a global navigation satellite system (GNSS) receiver arranged to obtain the location and / or speed of the user and a pedometer for counting steps made by the user. Data from the GNSS receiver is used to calibrate the pedometer each time the user is determined to travel a distance greater than a predefined distance value during a period of time in which signals obtained by the GNSS receiver meet the one or more accuracy and / or reliability criteria.

The invention discloses a sparse OFDM channel estimation method based on a generalized orthogonal matching tracking algorithm. The method comprises the following steps: step one, translating a channelestimation problem into a problem for reconstructing original signal based on the compressed sensing theory; step two, designing a measurement matrix; and step three, reconstructing the original signal by using the generalized orthogonal matching tracking method so as to finish the channel estimation. The sparse OFDM channel estimation method based on the generalized orthogonal matching trackingalgorithm in the compressed sensing disclosed by the invention comprises the steps of translating the channel estimation problem into the problem for reconstructing original signal based on the compressed sensing theory, designing the measurement matrix and reconstructing the original signal by using the generalized orthogonal matching tracking algorithm. The operation complexity, namely the running time, are greatly reduced, the impulse response of the channel is precisely estimated, the system performance of the OFDM sparse channel estimation is improved so as to improve the signal demodulation quality, and the method has high application value.

The invention discloses a broadband signal DOA estimation method based on a co-prime array, and the method comprises the steps: S1, designing a co-prime array structure through an antenna; S2, carrying out the sampling and discrete Fourier transform of a broadband signal received by an antenna in the co-prime array, and obtaining a frequency domain signal output model; S3, calculating an autocorrelation matrix of the frequency domain signal output model, carrying out the vectorization of the frequency domain signal output model, and obtaining a new signal model; S4, carrying out the processing of the new signal model, and obtaining a spatial smooth covariance matrix of the broadband signal; Sa5, dividing a space domain grid, constructing a dictionary, carrying out the sparse representation of the spatial smooth covariance matrix through employing the dictionaries of a plurality of frequency points of the broadband signal, and forming a multi-measurement-vector sparse representation model of a plurality of dictionaries of the broadband signal; S6, achieving the arrival direction estimation of the broadband signal in a mode of solving a sparse inverse problem through the joint sparse constraint of the sparse representation coefficients of the plurality of dictionaries. The method can improve the estimation precision of the direction angle of the broadband signal under the condition of low signal to noise ratio, and reduces the direction finding error.

An apparatus for estimating state variables of a secondary battery as an estimation target performs so that a neural network unit studies a true value of a battery temperature, a temperature large value which is larger than the true value of the battery temperature by an approximating temperature sensor detection error, and a temperature small value which is smaller than the true value of the battery temperature by the approximating temperature sensor detection error. After completion of the learning of those values, the neural network unit inputs a battery temperature detected by the temperature sensor, and performs a neural network based calculation to calculate a SOC (state of charge) of the secondary battery. This can drastically increase the calculation accuracy of the SOC of the secondary battery.

The invention provides a method and device for estimating a state of charge of a battery. The method comprises the following steps: establishing a multi-parameter fusion mathematical model of a lithium iron phosphate battery; using a fuzzy Kalman filtering algorithm based on an index input membership function to optimize and estimate the state of the charge of the battery, wherein the step of establishing the multi-parameter fusion mathematical model comprises establishing a charge-discharge multiplying power-state of charge sub module, a temperature-state of charge sub module, and a cycle index-state of charge sub module. The method for estimating the state of charge of the battery uses the fuzzy self-adaptive Kalman filtering algorithm based the index input membership function, so that the theoretical value of measurement noise in the Kalman filter is adjusted smoother in a self-adpative manner, thereby improving the matching degree of the system measurement noise, and estimating the state of the charge of the battery more accurately.