04622nam 2200601 450 991013504530332120230808205246.01-118-95689-31-5231-1046-51-118-95688-51-118-95687-7(CKB)4330000000007684(EBL)4622925(MiAaPQ)EBC4622925(Au-PeEL)EBL4622925(CaPaEBR)ebr11244272(CaONFJC)MIL945141(OCoLC)956648064(EXLCZ)99433000000000768420160901h20162016 uy 0engur|n|---|||||rdacontentrdamediardacarrierRadar data processing with applications /He You, Xiu Jianjuan, Guan XinSingapore :Publishing House of Electronics Industry :Wiley,2016.©20161 online resource (557 p.)Description based upon print version of record.1-118-95686-9 Includes bibliographical references and index.Title Page ; Copyright; Contents; About the Authors; Preface; Chapter 1 Introduction ; 1.1 Aim and Significance of Radar Data Processing; 1.2 Basic Concepts in Radar Data Processing; 1.2.1 Measurements; 1.2.2 Measurement Preprocessing; 1.2.3 Data Association; 1.2.4 Wave Gate; 1.2.5 Track Initiation and Termination; 1.2.6 Tracking; 1.2.7 Track; 1.3 Design Requirements and Main Technical Indexes of Radar Data Processors; 1.3.1 Basic Tasks of Data Processors; 1.3.2 The Engineering Design of Data Processors; 1.3.3 The Main Technical Indexes of Data Processors1.3.4 The Evaluation of Data Processors1.4 History and Present Situation of Research in Radar Data Processing Technology; 1.5 Scope and Outline of the Book; Chapter 2 Parameter Estimation ; 2.1 Introduction; 2.2 The Concept of Parameter Estimation; 2.3 Four Basic Parameter Estimation Techniques; 2.3.1 Maximum A Posteriori Estimator; 2.3.2 Maximum Likelihood Estimator; 2.3.3 Minimum Mean Square Error Estimator; 2.3.4 Least Squares Estimator; 2.4 Properties of Estimators; 2.4.1 Unbiasedness; 2.4.2 The Variance of an Estimator; 2.4.3 Consistent Estimators; 2.4.4 Efficient Estimators2.5 Parameter Estimation of Static Vectors2.5.1 Least Squares Estimator; 2.5.2 Minimum Mean Square Error Estimator; 2.5.3 Linear Minimum Mean Square Error Estimator; 2.6 Summary; Chapter 3 Linear Filtering Approaches ; 3.1 Introduction; 3.2 Kalman Filter; 3.2.1 System Model; 3.2.2 Filtering Model; 3.2.3 Initialization of Kalman Filters; 3.3 Steady-State Kalman Filter ; 3.3.1 Mathematical Definition and Judgment Methods for Filter Stability; 3.3.2 Controllability and Observability of Random Linear System; 3.3.3 Steady-State Kalman Filter; 3.4 Summary; Chapter 4 Nonlinear Filtering Approaches4.1 Introduction4.2 Extended Kalman Filter; 4.2.1 Filter Model; 4.2.2 Some Problems in the Application of Extended Kalman Filters; 4.3 Unscented Kalman Filter; 4.3.1 Unscented Transformation; 4.3.2 Filtering Model; 4.3.3 Simulation Analysis; 4.4 Particle Filter; 4.4.1 Filtering Model; 4.4.2 Examples of the Application of EKF, UKF, and PF; 4.5 Summary; Chapter 5 Measurement Preprocessing Techniques ; 5.1 Introduction; 5.2 Time Registration; 5.2.1 Interpolation/Extrapolation Method Using Velocity; 5.2.2 The Lagrange Interpolation Algorithm; 5.2.3 Least-Squares Curve-Fitting Algorithm5.3 Space Registration5.3.1 Coordinates; 5.3.2 Coordinate Transformation; 5.3.3 Transformation of Several Common Coordinate Systems; 5.3.4 Selection of Tracking Coordinate Systems and Filtering State Variables; 5.4 Radar Error Calibration Techniques; 5.5 Data Compression Techniques; 5.5.1 Data Compression in Monostatic Radar; 5.5.2 Data Compression in Multistatic Radar; 5.6 Summary; Chapter 6 Track Initiation in Multi-target Tracking ; 6.1 Introduction; 6.2 The Shape and Size of Track Initiation Gates; 6.2.1 The Annular Gate; 6.2.2 The Elliptic/Ellipsoidal Gate; 6.2.3 The Rectangular Gate6.2.4 The Sector GateRadarMathematicsRadarData processingRadarMathematics.RadarData processing.621.38480285He You1956-996072Xiu Jianjuan1971-Guan Xin1978-MiAaPQMiAaPQMiAaPQBOOK9910135045303321Radar data processing with applications2282702UNINA