213 results about "Radar observations" patented technology

A method and system for detecting an object uses a composite evidence grid based on dual frequency sensing. A source transmits a laser transmission in a first zone. A detector receives a reflection of the laser transmission from an object in the first zone to determine laser observed data associated with points on the object. A transmitter transmits a radar transmission in a second zone that overlaps with the first zone. A receiver receives a reflection of the radar transmission from an object in the second zone to determine radar observed data associated with points on the object. The laser observed data is processed to form a laser occupancy grid for the first zone and the radar observed data is processed to form a radar occupancy grid for the second zone. An evaluator evaluates the radar occupancy grid and the laser occupancy grid to produce a composite evidence grid for at least an overlapping region defined by the first zone and the second zone.

The invention discloses an ocean current field inversion satellite-borne SAR system based on angle diversity, and a method thereof. The satellite-borne SAR system comprises two radar antennas which are arranged in the flying direction of a satellite, wherein the two radar antennas respectively generate two radar wave beams; and the two wave beams have different squint angles and can irradiate the same area on the ocean surface in different time. The method comprises: utilizing the satellite-borne SAR system and taking a doppler center frequency as the observation variable to perform inversion on an ocean current field; and obtaining a complete velocity vector of an ocean current, that is, the ocean current information obtained through inversion not only includes the radial velocity information of the ocean current but also includes the azimuth velocity information. Compared with a traditional ocean surface current field inversion means, such as field observation and shore-base radar observation, the ocean current field satellite-borne SAR system based on angle diversity can realize inversion of a worldwide ocean current field, can comprehensively know about temporal and spatial variation of the ocean current, and can work all day long and all weather without limitation of meteorological conditions.

The invention discloses a linear frequency modulation radar signal processing method based on compressed sensing. The method comprises the steps of (1) emitting a linear frequency modulation signal to a radar and preprocessing an echo signal, which means that the deramping processing of the echo signal is carried out, a difference frequency signal is outputted, and a signal model of deramping processing is established in a time domain, (2) according to the sparsity of the difference frequency signal in a frequency domain, constructing a sparse conversion matrix, and establishing a sparse representation model of the radar echo signal, (3) constructing a measurement matrix, and realizing the projection transformation of a difference frequency sparse signal to a low dimensional space, and (4) using an orthogonal matching pursuit (OMP) algorithm, reconstructing a radar difference frequency signal, and efficiently obtaining target information. Accoding to the method, the compression of radar echo signal data can be fundamentally realized, the change of a sparse model according to a radar observation distance is not needed, finally the target information is obtained, and the method is suitable for the echo signal processing of an actual radar.

The invention relates to a high-precision tracking method applied to a non-engine maneuvering target. According to the method, firstly, a target motion model containing system adaptive parameters is built according to the non-zero mean time relevant random process characteristic met by the accelerated speed in the actual target motion; secondly, the target motion characteristic is predicated according to the built target motion model; then, the current state estimation value of the target is calculated through utilizing the target state predicating value and the radar observation data value; and finally, the system adaptive parameters are corrected according to the accelerated speed estimation value of the target, the corrected system adaptive parameters are utilized for updating the target motion model, and the updated target motion model is utilized for carrying out next predication and estimation. The method has the advantages that the target with the non-engine maneuvering random character realizes the online estimation, the accuracy of a maneuvering target model for describing the actual motion characteristics is improved, and the tracking precision of the non-engine maneuvering target is improved.

The invention discloses a non-convex optimization based MIMO radar moving object detection method. The method comprises the following steps: according to radar parameters, performing distance-angle-Doppler grid dividing on an observation area; according to radar emission, the position of a receiving array, and radar observation area parameters, calculating emission and reception guiding vectors; according to emission signal waveforms, the guiding vectors and a distance unit time delay transformation matrix, constructing a sparse dictionary matrix; performing serialization on echo signals received by an antenna array; and according to an aforementioned model, constructing MIMO radar moving object detection to be an optimization problem of an L[1/2] norm minimizing constraint; and using a heavy weight determining L[1] norm regularization method to solve the optimization problem, obtaining distance-angle-Doppler imaging of a MIMO radar moving object, and detecting a moving object in the observation area. By using the method provided by the invention, a moving object detection result more accurate than a result by use of a convex optimization algorithm can be obtained, and the detection result is higher in resolution.

The invention provides a metallic ball calibration method for an X-band solid dual-polarization weather radar, and the method comprises the steps: respectively selecting a test point in a broad pulse detection range and a narrow pulse detection range of the radar; placing a metallic ball at each test point; calculating a corresponding radar observation elevation angle, an radar observation azimuth angle and a radar observation database number for each metallic ball through employing the GPS information of each metallic ball and the longitude and latitude and height information of the radar; setting a calibration observation mode, and obtaining the observation data, wherein the calibration observation mode comprises the horizontal change range of a radar observation azimuth, the change range of the radar observation elevation angle and a stepping angle, and the observation data comprises a radar reflectivity factor observed value and a difference reflectivity factor observed value; and enabling the radar reflectivity factor observed value and the difference reflectivity factor observed value to be respectively compared with a reflectivity factor theoretical value and a difference reflectivity factor theoretical value, wherein the differences serve as the measurement error of the radar; and correcting the detection result of the radar in a corresponding detection range through the measurement error.

The invention provides a multichannel synthetic aperture radar SAR imaging method comprising the following steps: forming a multichannel radar observation equation Yi based on an echo simulation operator Mi (X) according to one-emission-multi-reception SAR echo data; forming a multichannel SAR imaging model based on sparse regularization according to the multichannel radar observation equation Yi; employing a threshold iteration algorithm to solve the multichannel SAR imaging model, and reconstructing observation scene backscattering coefficient X*, thereby obtaining a complex image of the observation scene. The multichannel synthetic aperture radar SAR imaging method can improve operation efficiency and reduce calculation cost.

The invention discloses a warning radar multi-target multi-channel parallel tracking processing method. The method comprises the steps that firstly, a parallel flight path tracking framework is built,and the tracking framework is divided into a plurality of non-interfering independent tracking channels; secondly, the target motion statistics and feature recognition means in the tracking channelsare used for automatically starting the flight path; then, according to motion feature setting relevance, filtering models and parameters of the different tracking channels, the official flight path is tracked, and a target likelihood function is used for performing flight path tracking quality evaluation; finally, on the basis of the parallel fusion framework and a flight path management strategy, the multi-channel tracking results are unified, and the comprehensive and accurate warning area target posture is obtained. The sea surface and aerial targets observed by a warning radar are dividedinto the multiple channels for finding and maintaining the flight path, and therefore the effects of comprehensively and accurately finding the targets, and tracking different types of targets in a high-precision and high-stability mode are achieved.

The invention discloses a dual linear polarization radar system. The dual linear polarization radar system comprise a data base module, a strong storm preprocessing module, a data matching and identification module, a strong storm processing module, a data correction module and a strong storm early-warning module. Time and space synchronization of a large-scale or specific-region weather system and collaborative observation of a fine structure are achieved by utilizing an efficient communication network application satellite navigation system adaptive to a weather radar network through an application of radar networking. High-definition GIS information and the collaborative observation are combined, quantitative time and space consistency of networking radar observation is achieved, and abilities to monitor and early warn disastrous weather such as strong rain are improved. The invention further provides a corresponding measurement method for the strong rain on a plateau by utilizing a dual linear polarization radar system network.

The invention provides a target combined positioning method based on Euler's distance means clustering, wherein the method comprises the steps of obtaining the position parameter of a target in a transmission coordinate system from observation data of each radar, obtaining the estimated amount of a target position parameter according to a simple track fusion method, calculating the Euler's distance between the positioning result of a single radar and a means clustering center, optimally determining the similarity among target position parameters by means of a fuzzy means clustering algorithm, fusing target position parameters according to a corresponding membership grade, and obtaining a target position parameter after fusion. The target combined positioning method has a simple computing model form and furthermore can effectively determine the spatial position of a flying target.

The invention provides an aerosol foundation data-based AOD (Aerosol Optical Depth) vertical correction effect evaluation method and system. The method comprises the steps of estimating a near-surface aerosol extinction coefficient and inverting the near-surface aerosol extinction coefficient based on observation data of a foundation visibility meter; inverting AOD based on observation data of a foundation sum photometer; inverting the near-surface aerosol extinction coefficient based on the visibility meter; performing vertical correction on the AOD based on a laser radar observation method or an atmospheric chemistry mode simulation method, and estimating the near-surface aerosol extinction coefficient according to a vertical correction result; and evaluating the effect and applicability of an AOD vertical correction method by comparing the difference between the estimated near-surface aerosol extinction coefficient with the inverted near-surface aerosol extinction coefficient. According to the method and the system, the errors caused by direct use of a satellite for AOD inversion and the evaluation uncertainty caused by a scale effect and the like can be avoided, so that the difficult problems in effect evaluation and applicability selection among various AOD vertical correction methods and various data sources are solved.

The invention relates to a road disastrous weather monitoring method. Based on design of an existing traffic weather station, Doppler meteorological radar observation data are introduced. By means of characteristics such as large range and high time resolution in the Doppler meteorological radar observation data, defects in existing road weather monitoring are settled, and coverage monitoring for no-monitoring areas without the traffic weather station is realized, thereby effective coverage rate and accuracy in road weather monitoring. The invention further relates to a vehicle early-warning method based on road disastrous weather monitoring. Furthermore a road disaster range is transmitted to drives on the road. In-advance early-warning in short time can be realized. Individualized vehicle condition information is combined with a disastrous weather risk, thereby realizing more accurate service to a vehicle user group, realizing efficient, in-time and accurate transmission of road emergent disastrous weather information to the vehicle drivers, and ensuring high driving safety on the road.

The application relates to a lightning forecasting method and system. The method comprises the steps of reading the latest electric field station observation data and radar observation data of an electric field station, and establishing a lightning proximity prediction model according to the electric field station observation data and the radar observation data; the establishing of the lightning proximity prediction model comprises the following steps: step a: setting an electric field amplitude threshold and an electric field difference threshold; step b: judging whether the read electric field station observation data reaches the set electric field amplitude threshold or the electric field difference threshold, and if the electric field station observation data reaches the set electric field amplitude threshold or the electric field difference threshold, performing step c; step c: determining whether the radar observation data before the current time reaches the preset threshold, ifthe radar observation data reaches the preset threshold, performing step d; and step d: generating a lightning warning graphic product and issuing lightning warning. The application realizes the beforehand release of thunderstorm early warning, and raises the capability and level of lightning forecast.

The invention discloses a tracking initiation method including radial velocity information for a circular motion target. The method comprises the following steps: first, based on motion features, establishing a continuous motion equation of the target, and converting the continuous motion equation of the target to a discrete motion equation; secondly, establishing a radar observing model which includes the radial velocity information in a polar coordinate system; thirdly, based on the features of a multiple frequency cw radar as described that the multiple frequency cw radar can not only obtain distance and angle information, but can also obtain velocity information, designing a tracking initiation gate which includes the radial velocity information; finally, configuring a tracing initiation flow chart which includes the radial velocity information. The method herein is applicable to radar systems which can provide velocity information, such as a multi-frequency cw radar system, a pulse Doppler radar system, etc. The method is also applicable to tracking initiation of a horizontal circular motion target, and can increase the effects of tracking initiation. In addition, the method herein is not only applicable to tracking initiation of horizontal circular motion, but is also applicable to other target motion patterns, and has excellent expansibility and value in popularization and application.

The invention discloses a method for initiating a radar target track based on random forest, and relates to a method for initiating a radar target track. The method aims at solving the problems of rough rule, poor accuracy, artificial setting of threshold value, and poor suitability to strong clutter environment in the existing visual method and logic method; larger calculation amount, multiple batches of data measuring, longer initiating time, and low target initiating probability on non-linear movement in a correction Hough conversion method and the like. The method specifically comprises the following steps of 1, extracting features from a point trace combination of historical observation data of radar to form a sample set D; sampling D, and forming n training sample collection sets; 2,training a t-th decision tree by the t-th training sample collection set, and forming a random forest combination classifier; 3, in the testing phase, performing data pre-selecting and feature extraction on the point traces of a radar observation area so as to obtain the track initiating result via the classifier. The method is suitable for the field of initiating of radar target tracks.

The invention provides a fractal dimension threshold iteration sparse microwave imaging method based on sparseness estimation. The method comprises the following specific steps: step 1, a radar observation model is established by using radar system parameters tested actually, and the sparseness estimation value of a target scene is calculated through the radar observation model; step 2, according to the sparseness estimation value, thresholds corresponding to striped areas of different orthogonal dimension coordinates are set self-adaptively, and the coordinate position of a strong point target is evaluated by using a fractal dimension threshold iteration method; step 3, based on the coordinate position of the strong point target, the back scattering coefficients of the target scene is recovered by using a least squares supported projection method to achieve microwave imaging. The method can obtain radar echo data under the downsampling condition, and high-quality and high-precision microwave images are reconstructed.

The invention discloses a method for detecting floating targets on the sea based on a normalized Doppler spectrum, and relates to the field of radar target detection. The method includes the steps that firstly, radar echo data are divided into blocks, and divided echo data are acquired; secondly, the normalized Doppler spectrum is calculated for the echo data of a unit to be detected; thirdly, the detection statistical amount is constructed according to the normalized Doppler spectrum; fourthly, a false alarm probability is given, and a detection threshold is acquired through a Monte Carlo experiment; fifthly, whether the targets exist or not is judged according to the detection statistical amount and the detection threshold, if the detection statistical amount is larger than the detection threshold, it is judged that the targets exist, or else it is judged that the targets do not exist. The method mainly solves the problems that in the prior art, detection performance is low when radar observation time is short. The method is adaptive, suitable for different sea states and space-time changes, and capable of effectively detecting the floating targets under the seat clutter background.

The invention provides a target tracking-before-detecting method based on Gaussian cardinalized probability hypothesis density filter, comprising the following steps: initializing: letting k represent a k time wherein k starts from one and belongs to a set of 1, 2,...,D; determining Nk targets corresponding to the k time; recording the moving state of the pth target at the k time as what is described in the figure; calculating the likelihood function corresponding to the intensity of the moving state Xk of the Nk targets at the (i,j) position contained in a radar observation area in the k-time Cartesian coordinate system under the moving state of the pth target at the k time; then calculating the average state estimations of the Nk targets at k time and the covariance estimations of the Nk targets at k time; and calculating in sequence the probability pk(Nk) of the target number (Nk) at the k time and the estimated value of the targets Nk contained in the radar observation area Nx X Ny in the k-time Cartesian coordinate system; letting one added to k to obtain the estimated value of target N1 included in the radar observation area Nx X Ny in the Cartesian coordinate system at 1 time to the estimated value of the target number ND included in the radar observation area Nx X Ny in the Cartesian coordinate system at D time.

The invention provides an error joint estimation method for a GM-EPHD filtering radar system based on ADS-B data. Firstly, the ADS-B observed values of a target is converted in a rectangular coordinate system with the position of a radar station as a center thereof to establish an ADS-B and radar observation equation of the target. A state transition equation of the target and the radar system error is established in the linear gaussian condition, and the radar system error is expanded to a target state to form an extended state. The gaussian hybrid-probability assumed density filtering on the target state is conducted by utilizing the ADS-B observed values after the coordinate transformation process, so that an accurate estimation on the target state is obtained. After that, the gaussian hybrid-probability assumed density filtering on the target state is conducted on the extended state after the updating of the target state by utilizing radar observation data. Furthermore, the joint estimation of the target state and the radar system error is conducted by a two-step kalman filter. Finally, the fusion estimation result of the radar system error is obtained through the weighted average algorithm. The method is high in estimation accuracy and good in estimation performance.

The invention discloses an observation method of a millimeter wave weather radar. The observation method of the millimeter wave weather radar comprises the specific steps that (1) a millimeter wave weather radar observation platform is set up, wherein the millimeter wave weather radar observation platform comprises an industrial control computer (1), an observation strategy setting module (2), an observation strategy scheduling module (3), an information acquisition module (4), an antenna controller (5) and a signal processor (6); (2) observation strategy parameters are set by the observation strategy setting module (2); (3) the observation strategy scheduling module (3) has control over the execution sequence of observation strategies, and carries out scheduling on the execution sequence of the observation strategies; (4) the information acquisition module (4) acquires antenna position information and echo processing signals of the millimeter wave weather radar. Therefore, observation of the millimeter wave weather radar is achieved. According to the observation method of the millimeter wave weather radar, setting of observation parameters is comprehensive and flexible, the control function is good, information of a weather object of an omnibearing three-dimensional space can be automatically obtained, weather data are complete, observation efficiency is high, and it is ensured that the requirement for research and application of the weather objects such as cloud is met.

The invention provides a Slam method based on prior information. The method includes the steps of: 1) adding an initial pose node, extracting primary feature of initial radar observation, marking keyfeatures, adding a feature node to a map, and calculating the constraint and weight of the feature node and the initial pose node; 2) extending the map by means of observation, the prior information and the key features; 3) when the last frame of radar observation information is added to the map, performing global optimization to obtain a route and a feature map; 4) establishing a raster map of the environment on the basis of a Bayesian filter according to the route, which is obtained through the final optimization, of a movable robot and observation corresponding to every pose. The prior information is introduced through the expandable feature hierarchy, so that the method can adapt different environments and prior information in different types; besides the structural features, the key features are also considered, and the framework and size of the environment are further constrained by means of the extra constraint among the key features, thus reducing accumulated error.

The invention discloses a method for eliminating a false target under radar networking, and belongs to the technical field of radar target information processing, which is used for solving the problems that when existing multiple networking radars are used for observing the same region, a false target is generated because the precisions of the radars are different and the target position data acquired by the multiple radars are different, and further the correct judgment of the current battlefield situation is affected. According to the key point of the technical scheme, the method comprises the following steps: constructing a universal radar communication protocol mold plate, and acquiring the radar target data by utilizing the communication protocol mold plate; associating target data information; measuring the target data similarity; and integrating the target data after the target data similarity is measured. According to the invention, the false target generation probability is reduced by around 50%, and the false target generation probability under the radar networking condition is reduced. The method is mainly applied to the military radar target information processing process, and also can be extensively applied to the multi-sensor information integration process in the measurement process.