37 results about "Sequential filter" patented technology

The invention discloses an application for detecting and tracking an infrared weak object under a complicated background. The application is characterized by comprising the following steps of: 1. suppressing clutters and keeping the topological structure of an image, and constructing a bionic vision weighted entropy model with an adjacent airspace and a preferred direction to realize conversion for the image from a grey mode to an entropy model; 2. analysing the movement state of the weak object with burst and stationary characteristics, and constructing a self-adaptive entropy flow target movement estimation model meeting the maneuvering features of the weak object by virtue of the nonlinear diffusion smoothing and self-adaptive local restriction criterion of an entropy flow to realize the approximation of an estimation speed to the real movement state of the weak object; 3. searching a weak object tracking method adopting generic multi-feature and measurement, and constructing a multi-feature fused sequential filter model to realize accurate, robust and real-time identification for the weak object. The invention discloses a self-adaptive entropy flow detection and tracking algorithm for the infrared weak object, and enriches a detection and tracking technology for the weak object.

An ordered list of precedence values includes a number of blocks of precedence values. An operating system receives filters from an application. The operating system assigns a precedence value to each filter from the available block of precedence values that has the highest priority. Precedence values are assigned to maintain a precedence order specified by the application. Filters and their assigned precedence values are communicated to an entity that filters packets by applying the filters in the order of their precedence values. Filters for an application can be added, deleted, or modified without affecting the precedence values of other filters for other applications. If an assignment is to be made when the lowest priority block is not available, then a repacking operation is performed to fill unused blocks in the list. The repacking is performed to reduce signaling associated with communicating reassigned precedences values to the filtering entity.

An observation lock detector block receives I&Q correlations and generates error measurement vectors, each including phase, frequency, code, pseudorange, and covariance residual estimates, and generates validity indicator and confidence indicator vectors, one of which error measurement vectors is an output as a selected error measurement vector with a respective validity indicator and confidence indicator vector, both of which selected vectors are communicated to a navigation solution processor in a ultratightly coupled navigation system for providing improved estimations of a navigation solution, the indicators indicating the usefulness of measurement errors, the prefilter detector block comprising discriminators, sequential filters, observation lock detectors and a measurement selector for selecting measurement vector based on phase, frequency, and code discriminations, the measurement errors being residual estimates that are indicated as valid or invalid for dynamic propagation of the residuals in a navigation receiver for improved performance, especially in low signal-to-noise environments, such as, for use in an ultratight GPS navigation system.

Sequential GPS Doppler carrier phase count measurements are used for precision sequential determination of position and velocity of a GPS receiver, such as for orbit determination and geolocation, with minimum throughput time. Real-time orbit determination and geolocation performance is enabled with an optimal sequential filter, and near-real-time performance is enabled with an optimal fixed-lag smoother. Many problems associated with prior art orbit determination are eliminated by addressing the “cycle slip” problem, the unknown initial range problem with RANGE^CP measurement representations, the problem of serial correlation in the measurements due to reprocessing of overlapping thermal noise. Also, the present invention significantly attenuates the carrier signal phase variation due to rotation of receiver antenna relative to transmitter antenna because the sequential phase count time intervals are sufficiently short.

The invention discloses a particle filter centralized tracking method for multi-base radar out-of-sequence measurement fusion, which belongs to the technical field of data fusion of multi-base radar systems. According to the invention, out-of-sequence measurement is sequentially used to update all states between the out-of-sequence measurement generation time and the latest sequential filter time,and particle filtering is used to achieve target tracking; the problem of deterioration of target fusion tracking performance, which is caused by radar measurement out-of-sequence caused by differentdata processing time of a radar station and communication link delay, is overcome; whether the current measurement is sequential measurement is judged; if the current measurement is sequential measurement, sequential measurement update is carried out, and otherwise out-of-sequence measurement fusion is carried out; the problem of out-of-sequence measurement of multiple arbitrary timing sequences,which is caused by different data preprocessing time of each radar station and communication link delay in a multi-base radar system is effectively solved; and a universal solution is proposed for the problem of out-of-sequence measurement of multiple arbitrary timing sequences, which has higher fusion precision than direct neglect of out-of-sequence measurement.

A method and apparatus for extracting oil from water, particularly spillage water from gasoline stations and water that emanates from vehicle-washing plants. The method and apparatus utilize filters to which contaminated water from the vehicle-washing plant and other contaminated water is passed. The water is cleansed in one or more mutually sequential filters arranged in the flow direction of the water. The water is cleansed by first causing the water to flow through a collection filter in which oil and coarse particles are collected in a first cleansing stage. The water from the collection filter is passed through a fine filter adapted to lower the oil content of the water to a level below about 50 to 70 mg/l in a second cleansing stage. The water from the fine filter then flows through a membrane filter that is adapted to filter-off at least 75% of the oil remaining in the water during a third cleansing stage. At least a substantial part of at least the water cleansed in the membrane filter is recycled back to the vehicle-washing plant while any residual part of that water is discharged to a municipal sewage network.

The invention discloses a fluorescence imaging surgical navigation system, which comprises an illumination light source, an excitation light source, an imaging optical module, a fixed filter module, adynamic filter module, an image acquisition module, a control module and a display module. The invention adopts a single camera combined with a sequential filter system, which breaks through the shortcoming that the conventional single camera can only obtain fluorescence images, and at the same time, compared with the traditional dual camera imaging system, the structure is simpler, compact, andthe cost is lower, and the use scenes of different fluorescence probes and a plurality of fluorescence probes are easy to be expanded.

The invention provides a handheld pan-tilt attitude estimation method based on extended Kalman filtering. The method comprises the following steps: step 1, selecting a state vector of an attitude estimation system, and constructing a prediction equation of the state vector; step 2, calculating a Jacobian matrix of a measurement prediction value according to a measurement prediction equation, the matrix being a measurement matrix, and completing establishment of an attitude estimation system model; and step 3, writing the extended Kalman filter into a sequential filtering form to complete handheld pan-tilt attitude estimation. According to the handheld pan-tilt attitude estimation method based on the extended Kalman filtering, firstly, the attitude estimation state model is established; secondly, a measurement model is established; finally, filtering parameters are designed according to the selected sensor, the extended Kalman filtering is performed in a sequential filtering form and the high-precision attitude information and speed information of the handheld pan-tilt are outputted.

The invention relates to a step-by-step fusion method of a multi-feedback lift signal of a rolling stabilizing fin. The method comprises the steps that an A/D module is used for collecting a lift signal and a fin angle signal of the rolling stabilizing fin; initial fusion lift is resolved using a sequential fusion method, and the mean square error of a lift measuring signal and the initial fusionlift is resolved; a fin angle converting force is resolved by using a linear switching method, and the mean square error of the fin angle converting force and the initial fusion lift is resolved; theabove resolved mean square errors are compared, and a reliable lift signal is retained; ridge estimation is used for further fusing the lift signal to obtain an ultimate fusion lift signal; a mean square error of the ultimate fusion lift signal and the actual lift signal is resolved to be compared with the previously resolved mean square errors, and the accuracy of the invented lift fusion methodis verified. The method has the advantages that the fusion speed can be accelerated by the designed sequential filter algorithm, faulted or missed detecting lift signals can be removed, the reliability of the system can be improved by adopting the ridge estimation fusion algorithm, and the accuracy and effectiveness of the fusion method can be verified through simulation experiments.

The invention discloses an unmanned aerial vehicle integrated navigation method and system based on unscented Kalman filtering, and the method can achieve the estimation of the position, speed and attitude of an unmanned aerial vehicle through an integrated navigation algorithm. Compared with an integrated navigation algorithm based on Kalman filtering and expansion Kalman filtering of the same dimension, the integrated navigation algorithm provided by the invention has higher precision; the integrated navigation algorithm provided by the invention can be used as another standby algorithm in a navigation system to perform redundancy design, so that the stability of the system is improved; according to the invention, a sequential filtering mode is adopted, the calculated amount in an embedded system can be reduced, and the requirement for configuration is lowered.