| 序号 | 专利名 | 申请号 | 申请日 | 公开（公告）号 | 公开（公告）日 | 发明人 |
|---|---|---|---|---|---|---|
| 1 | 一种雷达目标测试方法 | CN201710683967.8 | 2017-08-11 | CN107505617A | 2017-12-22 | 王治家; 叶德焰; 任赋; 林雅; 林文畅 |
| 本发明涉及雷达测试领域，特别地涉及一种雷达目标测试方法。本发明公开了一种雷达目标测试方法，包括如下步骤：S1，对雷达输出的原始目标进行筛选，挑选出有效目标；S2，通过目标跟踪算法，从有效目标中得出跟踪目标；S3，当车辆驶入弯道时，通过弯道算法，对跟踪目标的相对位置进行估计；S4，将雷达输出的有效目标和跟踪目标的极坐标信息转换为直角坐标信息；S5，根据有效目标和跟踪目标的直角坐标信息在航迹界面上分别显示有效目标航迹和跟踪目标航迹以进行对比，根据对比结果得出雷达目标测试结果。本发明为雷达应用测试提供便利，大大提高了雷达应用测试效率。 | ||||||
| 2 | 一种多输入多输出雷达波形设计方法 | CN201510346063.7 | 2015-06-19 | CN104898113A | 2015-09-09 | 赵宜楠; 赵占锋; 冯翔; 周志权 |
| 一种多输入多输出雷达波形设计方法，属于雷达通信技术领域。本发明的目的是提供一种具有更低的相关旁瓣和频谱抑制深度，且效率高、耗时少、并具有较高的鲁棒性、具有良好时频抗干扰性能的设计方法。根据雷达场景中强散射体与待测目标的相对位置，预估自相关旁瓣抑制模糊区间，进而构造相应的目标函数；分析MIMO雷达波形正交性约束，构造满足正交性约束的目标函数；根据场景先验信息预估频域干扰模糊频带区间，进而构造相应目标函数；构造恒模相位编码波形约束条件；构造松弛交替投影算法框架；根据所提松弛交替投影算法框架求解波形设计，给出三种波形优化输出方式。采用松弛交替投影恒模波形编码设计，可使MIMO雷达具有更好的检测性能。 | ||||||
| 3 | Compressive Coded Antenna/Meta-Antenna | US15562349 | 2016-03-31 | US20180356515A1 | 2018-12-13 | Jose Angel Martinez-Lorenzo |
| A system for sensing a target in a region of interest (ROI) includes a coded compressive antenna (CCA) to generate an EM field codified in multiple dimensions. One or more receivers receives EM energy reflected by the target, and produces reflection information corresponding to the reflected energy. A compressive sensing imaging processor analyzes reflection information to generate an image representing the target. The CCA may use a distorted reflector, a vortex lens, and/or meta-materials to codify the EM field in multiple dimensions. The system may evaluate a sensing matrix that characterizes the transmission channel and the codified EM field. The system configures the CCA to produce a coded EM field enhances certain sensing matrix singular values, with respect to an EM field produced by a non-codified antenna. The sensing system provides increased target sensitivity while reducing false detections. | ||||||
| 4 | Integrated rainfall estimation method using X-band dual-polarimetric radar measurement data | US14307792 | 2014-06-18 | US09348015B2 | 2016-05-24 | Sang Hun Lim |
| An integrated rainfall calculation method using X-band dual-polarimetric radar measurement data includes a precipitation classification step of classifying hydrometeors into four types of snow, rain/snow, rain and non-meteorological target through a fuzzy logic technique using a correlation coefficient (cross correlation coefficient, ρhv), features of a measured differential propagation phase (Ψdp(r)) or differential propagation phase (φdp) and a signal-to-noise ratio (SNR) as input variables (input feature vector); a specific differential phase calculation step of separately calculating a specific differential phase by applying a specific differential phase using a total difference of differential phase and signal-attenuation corrected reflectivity for the rain among the classified hydrometeors and applying a specific differential phase calculated using a filtering method for the other hydrometeors; and a rainfall calculation step of calculating rainfall by using a relation between the specific differential phase and the rainfall and using the separately calculated specific differential phase. | ||||||
| 5 | INTEGRATED RAINFALL ESTIMATION METHOD USING X-BAND DUAL-POLARIMETRIC RADAR MEASUREMENT DATA | US14307792 | 2014-06-18 | US20150145717A1 | 2015-05-28 | Sang Hun LIM |
| An integrated rainfall calculation method using X-band dual-polarimetric radar measurement data includes a precipitation classification step of classifying hydrometeors into four types of snow, rain/snow, rain and non-meteorological target through a fuzzy logic technique using a correlation coefficient (cross correlation coefficient, ρhv), features of a measured differential propagation phase (Ψdp(r)) or differential propagation phase (φdp) and a signal-to-noise ratio (SNR) as input variables (input feature vector); a specific differential phase calculation step of separately calculating a specific differential phase by applying a specific differential phase using a total difference of differential phase and signal-attenuation corrected reflectivity for the rain among the classified hydrometeors and applying a specific differential phase calculated using a filtering method for the other hydrometeors; and a rainfall calculation step of calculating rainfall by using a relation between the specific differential phase and the rainfall and using the separately calculated specific differential phase. | ||||||
| 6 | Method and Apparatus for Enhanced Multi-Node Utilization of an Electromagnetic State Space | US14078997 | 2013-11-13 | US20150130656A1 | 2015-05-14 | Harry Marr; Charles T. Hansen; Brian Pierce |
| Methods and systems are provided for efficiently packing nodes within an electromagnetic state space. | ||||||
| 7 | Method Of Estimating Equivalent Radar Cross Section On The Basis Of Near-Field Measurements | US14127167 | 2012-06-13 | US20140172389A1 | 2014-06-19 | Sylvain Morvan; Olivier Vacus |
| A method for estimating the equivalent radar cross section (RCS) of an object using near-field measurements. The method using a diffraction model of the object in far field and a diffraction model in near field. These models make it possible to determine respectively bases adapted to said object in far field and in near field. The measurement vector is first of all projected onto the base adapted in near field and the components obtained are transformed into components on the base in far field. The vector obtained is then returned into the analysis base of the RCS in order to provide a reconstructed vector. The components of the reconstructed vector are next used for calculating the RCS. | ||||||
| 8 | Continuously adaptive dynamic signal separation and recovery system | US08990682 | 1997-12-15 | US06236862B1 | 2001-05-22 | Gamze Erten; Faihi M. Salam |
| A method and apparatus for dynamically separating and recovering original signal sources by processing a set of mixed received mixtures and convolution of said signals utilizing differential equations and a computer. The system of the invention enables the blind separation and recovery of an unknown number of signals mixed together in dynamically changing interference environments with very minimal assumption on the original signals. The system of this invention has practical applications to nonmultiplexed media sharing, adaptive interferer rejection, acoustic sensors, acoustic diagnostics, medical diagnostics and instrumentation, speech, voice, language recognition and processing, wired and wireless modulated communication signal receivers, and cellular communications. | ||||||
| 9 | MÉTHODE D'ESTIMATION DE SURFACE ÉQUIVALENTE RADAR À PARTIR DE MESURES EN CHAMP PROCHE | EP12730836.9 | 2012-06-13 | EP2721430A1 | 2014-04-23 | MORVAN, Sylvain; VACUS, Olivier |
| The present invention relates to a method of estimating equivalent radar cross section (RCS) of an object with the aid of near-field measurements, the method using a model of far-field diffraction of the object and a model of near-field diffraction. These models make it possible to determine respectively bases suited to said object for far field and for near field. The vector of measurements is firstly projected onto the basis suitable for near field and the components obtained are transformed into components on the far-field basis. The vector obtained is then reduced to the RCS analysis basis to provide a reconstructed vector. The components of the reconstructed vector are then used for the calculation of the RCS. The invention also relates to a computer program for implementing said method of estimation. | ||||||
| 10 | CHIRP TRAVELLING WAVE SOLUTIONS AND SPECTRA | EP15870489.0 | 2015-02-13 | EP3234636A1 | 2017-10-25 | Guruprasad, Venkata |
| Spectral components of waves having one or more properties other than phase and amplitude that vary monotonically with time at a receiver, and provide retardations or lags in the variation in proportion to the times or distances travelled from the sources of the waves to the receiver. The lags denote the property values prior to departure from a source and are absent in its proximity. Orthogonality of the lags to modulated information makes them useful for ranging and for separation or isolation of signals by their source distances. Lags in frequencies and wavelengths permit multiplication of capacities of physical channels. Constancy of the lagging wavelengths along the entire path from a source to the receiver enables reception through channels or media unusable at the source wavelengths, as well as imaging at wavelengths different from the illumination. | ||||||
| 11 | MÉTHODE D'ESTIMATION DE SURFACE ÉQUIVALENTE RADAR À PARTIR DE MESURES EN CHAMP PROCHE | EP12730836.9 | 2012-06-13 | EP2721430B1 | 2015-08-05 | MORVAN, Sylvain; VACUS, Olivier |
| 12 | Verfahren zur Detektion von Peaküberlagerungen in einem diskreten Spektrum eines Ortungssignals | EP09171448.5 | 2009-09-28 | EP2182380B1 | 2011-07-20 | Heilmann, Stefan; Gross, Volker; Leinbaum, Stephan; Kuehnle, Goetz; Bechler, Dirk |
| The method involves determining a width dimension at the peak depending on the approximation function. A point is located in a diagram and determines a distance. The probability is evaluated depending on the distance. The peak is approximated by the continuous function and a frequency line correction depending on the peak of the approximated function. An independent claim is included for a driver assistance system for a motor vehicle. | ||||||
| 13 | Verfahren zur Detektion von Peaküberlagerungen in einem diskreten Spektrum eines Ortungssignals | EP09171448.5 | 2009-09-28 | EP2182380A1 | 2010-05-05 | Heilmann, Stefan; Gross, Volker; Leinbaum, Stephan; Kuehnle, Goetz; Bechler, Dirk |
Verfahren zur Detektion von Peaküberlagerungen in einem diskreten Spektrum eines Ortungssignals, bei dem ein im diskreten Spektrum erkannter Peak (36) durch eine stetige Funktion approximiert wird und anhand der Lage des Scheitels der approximierenden Funktion eine Frequenzlinienkorrektur δk bestimmt wird, dadurch gekennzeichnet, daß anschließend die folgenden Schritte ausgeführt werden: |
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| 14 | TIME-OF-FLIGHT (TOF) CAPTURING APPARATUS AND IMAGE PROCESSING METHOD OF REDUCING DISTORTION OF DEPTH CAUSED BY MULTIPLE REFLECTION | US15713149 | 2017-09-22 | US20180089847A1 | 2018-03-29 | Jisan LEE; Yonghwa PARK |
| An image processing method for reducing distortion of a depth image may include: obtaining a plurality of original images based on light beams which are emitted to and reflected from a subject; determining original depth values of original depth images obtained from the plurality of original images, based on phase delays of the light beams, the reflected light beams comprising multi-reflective light beams that distort the original depth values; determining imaginary intensities of the multi-reflective light beams with respective to each phase of the multi-reflective light beams, based on regions having intensities greater than a predetermined intensity in the original depth images; correcting the original depth values of the original depth images, based on the imaginary intensities of the multi-reflective light beams; and generating corrected depth images based on the corrected original depth values. | ||||||
| 15 | Training Algorithm For Collision Avoidance Using Auditory Data | US15183610 | 2016-06-15 | US20170364776A1 | 2017-12-21 | Ashley Elizabeth Micks; Jinesh J. Jain; Kyu Jeong Han; Harpreetsingh Banvait |
| A machine learning model is trained by defining a scenario including models of vehicles and a typical driving environment. A model of a subject vehicle is added to the scenario and sensor locations are defined on the subject vehicle. A perception of the scenario by sensors at the sensor locations is simulated. The scenario further includes a model of a parked vehicle with its engine running. The location of the parked vehicle and the simulated outputs of the sensors perceiving the scenario are input to a machine learning algorithm that trains a model to detect the location of the parked vehicle based on the sensor outputs. A vehicle controller then incorporates the machine learning model and estimates the presence and/or location of a parked vehicle with its engine running based on actual sensor outputs input to the machine learning model. | ||||||
| 16 | Phase Retrieval Algorithm for Generation of Constant Time Envelope with Prescribed Fourier Transform Magnitude Signal | US15102740 | 2013-12-11 | US20160363658A1 | 2016-12-15 | Guillaume ALLEON; Kaushal JADIA; Rajan SRINIVASAN; Avik SANTRA |
| The invention is an iterative process for performing iteratively the phase retrieval of an adaptive signal x(t) matching two sets of constraint both concerning the time envelope ue(t) of signal x(t) and magnitude distribution Um(f) of its spectral representation. At each iteration k the process computes an estimate {tilde over (x)}k(t) of signal x(t) which is obtained from a first projection PA on a first set of constraint in time domain of a computed value xk(t) of x(t), xk(t) deriving from an estimate {tilde over (X)}k-1(f) of the spectrum of signal x(t), said estimate {tilde over (X)}k-1(f) being itself obtained from a second projection PB on a second set of constraints in spectral domain of the Fourier transform Xk(f) of the estimate {tilde over (x)}k-1(t) of x(t) computed at iteration k−1. Iterative computation of estimate {tilde over (x)}k(t) is repeated until {tilde over (x)}k(t) meets a predefined criterion which indicates that estimate {tilde over (x)}k(t) is close enough to expected signal x(t). | ||||||
| 17 | METHODS AND APPARATUS FOR 3D RADAR DATA FROM 2D PRIMARY SURVEILLANCE RADAR AND PASSIVE ADJUNCT RADAR | US13721233 | 2012-12-20 | US20160025849A1 | 2016-01-28 | Jian Wang; Eli Brookner; Peter R. Drake; Bradley Fournier; Anthony M. Ponsford; Yueh-Chi Chang |
| Methods and apparatus for combining radar signals of a two-dimensional primary radar covering a surveillance area and a passive adjunct radar to provide three-dimensional data for targets and weather. In exemplary embodiments, high beam and low beam data from the primary radar and elevation data from the adjunct radar can be used to mitigate interference from clutter, such as wind farms. | ||||||
| 18 | Method and Apparatus For Self Calibration of A Vehicle Radar System | US14020053 | 2013-09-06 | US20150070207A1 | 2015-03-12 | Jeffrey Millar; David Insana; Christian Sturm; Kevin Krupinski |
| A radar sensor for use within a vehicle includes self calibration functionality for performing angle calibrations for the sensor when the sensor is mounted within the vehicle. In at least one embodiment, the radar sensor collects information on stationary infrastructure around the vehicle for use in calibration operations. The infrastructure information may be used to generate a Doppler Monopulse Image (DMI) or other graph for the sensor. A clutter ridge within the DMI or other graph may then be analyzed to determine calibration data for the sensor. | ||||||
| 19 | SYSTEM AND METHOD FOR DISTRIBUTION FREE TARGET DETECTION IN A DEPENDENT NON-GAUSSIAN BACKGROUND | US13912596 | 2013-06-07 | US20140361919A1 | 2014-12-11 | Andrew J. Pomerance; Richard Hugh Anderson; Kurt James Lightner; Katherine S.H. Johnson |
| A method for target detection includes: receiving input data via an input signal; generating a histogram from the received data by a processor; rank-ordering the received data based on power or amplitude of the received input signal; comparing the ranked data received in a current time period to the ranked data received in a previous time period to calculate a Bivariate Conditional Exceedance function (BCEF); utilizing the calculated BCEF to estimate a Gumbel Copula parameter; accumulating a log-likelihood statistic from the estimated Gumbel Copula parameter and the generated histogram; comparing the log-likelihood statistic with a threshold value; and determining a detection of the target, when the log-likelihood statistic is below the threshold value. | ||||||
| 20 | High-order high-frequency rough surface scattering solver | US09675942 | 2000-09-29 | US06600566B1 | 2003-07-29 | Maria Z. Caponi; Alain Sei; Oscar P. Bruno |
| The present invention provides a rough surface scattering method and solver for efficiently computing electromagnetic scattered fields resulting from an incident wave (12) being reflected from a surface slowly varying on the scale of the wavelength (10). The wavelength claimed approach to high-frequency scattering is based on the use of expansions of high order in parameter &lgr;, wavelength of the incident radiation. The resulting high-order expansion approach expands substantially on the range of applicability over low order methods, and can be used in some of the most challenging cases arising in applications. The surface current (14) induced by the incident wave (12) is represented as a high-order high-frequency expansion (20). The surface current ansatz is substituted into the surface current integral equation (22), wherein a surface current series expansion is formed (24) having, a high frequency order. The surface current series expansion includes an oscillatory integral and surface current coefficients. An asymptotic expansion of the oscillatory integral is produced having a Taylor series (26). The Taylor series is evaluated and the surface current coefficients (32) determined. The surface current coefficients are inserted into the surface current series expansion. The surface current series expansion is evaluated to yield the surface current (36). Finally, the scattered field is computed based upon the solved surface current (36). | ||||||
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