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多傳感器編隊目標跟蹤技術 ( 簡體 字) |
| 作者：王海鵬,董云龍,熊偉等 | 類別：1. -> 教材 -> 數位影像處理 |
| 譯者： |
| 出版社：電子工業出版社 |  3dWoo書號： 46297
詢問書籍請說出此書號！【缺書】
NT售價： 290 元 |
| 出版日：1/1/2017 |
| 頁數：224 |
| 光碟數：0 |
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| 印刷：黑白印刷 | 語系： ( 簡體 版 ) |
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| ISBN：9787121299469 |
| 作者序 | 譯者序 | 前言 | 內容簡介 | 目錄 | 序 |
| (簡體書上所述之下載連結耗時費功, 恕不適用在台灣, 若讀者需要請自行嘗試, 恕不保證) |
| 作者序： |
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前言：多傳感器編隊目標跟蹤技術是現階段目標跟蹤領域的研究重點和難點之一。
本書以國家自然科學基金資助項目、山東省自然基金資助項目為背景依托，針對
編隊目標跟蹤領域中的一些關鍵問題進行了深入研究，提出了多種新的、便于工
程應用的多傳感器編隊目標跟蹤算法。
全書共分6 章，第1 章介紹了多傳感器編隊目標跟蹤的研究背景、國內外研
究現狀、以及一些有待解決的關鍵問題。第2 章介紹了編隊航跡目標起始算法，
為解決編隊內目標難以正確起始的問題，提出了基于相對位置矢量的編隊目標灰
色航跡起始算法、集中式多傳感器編隊目標灰色航跡起始算法和基于運動狀態的
多傳感器編隊目標航跡起始算法。第3 章介紹了復雜背景下集中式多傳感器編隊
目標跟蹤算法，為解決復雜背景下多傳感器非機動編隊內目標的跟蹤問題，首先
基于群分割中圖像法的思想建立了云雨雜波剔除模型和帶狀干擾剔除模型，然后
基于相鄰時刻同一編隊內目標真實回波空間結構相對固定的特性，分別提出了基
于模板匹配的集中式多傳感器編隊目標跟蹤算法和基于形狀方位描述符的集中式
多傳感器編隊目標粒子濾波算法。第4 章介紹了集中式多傳感器機動編隊目標跟
蹤算法，為解決多傳感器探測下無法正確跟蹤機動編隊內目標的問題，首先建立
了整體機動、分裂、合并、分散四種典型機動模式下的編隊目標跟蹤模型，然后
提出了變結構JPDA 機動編隊目標跟蹤算法和擴展廣義S-維分配機動編隊目標跟
蹤算法。第5 章介紹了系統誤差下編隊目標航跡關聯算法，為解決系統誤差下編
隊內目標的跟蹤問題，提出了基于雙重模糊拓撲的編隊目標航跡關聯算法和基于
誤差補償的編隊目標航跡關聯算法。第6 章回顧和總結本書的研究成果，并對某
些問題提出進一步的研究建議。
本書由煙臺海軍航空工程學院王海鵬、 編著。多傳感器編隊目標跟蹤技
術是一個信息融合領域的一個研究熱點，本書不可能對這個領域的發展做出統攬
無余的介紹。為此，我們在本書最后一章對一些新的研究思路進行了展望，供讀
者進一步研究參考。同時，由于編著者水平有限，書中難免還存在一些缺點和錯
誤，殷切希望廣大讀者批評指正。 |
內容簡介：本書是關于多傳感器編隊目標跟蹤方法的一部專著，是作者們對國內外近30年來該領域研究進展和自身研究成果的總結。全書由6章組成，主要內容有：基礎知識概述，編隊目標航跡起始方法，復雜背景下集中式多傳感器編隊目標跟蹤方法，集中式多傳感器機動編隊目標跟蹤方法，系統誤差下編隊目標航跡關聯方法，建議與展望。 |
目錄：第1章 緒 論············ 1
1.1 研究背景············· 1
1.2 國內外研究現狀··········· 2
1.2.1 航跡起始··········· 2
1.2.2 航跡維持··········· 3
1.2.3 機動跟蹤··········· 3
1.3 多傳感器編隊目標跟蹤技術中有待解決的一些關鍵問題··· 4
1.3.1 雜波環境下編隊目標航跡起始技術······ 4
1.3.2 復雜環境下集中式多傳感器編隊目標跟蹤技術···· 5
1.3.3 集中式多傳感器機動編隊目標跟蹤技術······ 5
1.3.4 系統誤差下編隊目標航跡關聯技術······ 6
1.4 本書的主要內容及安排········· 7
第2章 編隊目標航跡起始算法·········· 8
2.1 引言············· 8
2.2 基于相對位置矢量的編隊目標灰色航跡起始算法····· 8
2.2.1 基于循環閾值模型的編隊預分割······ 10
2.2.2 基于編隊中心點的預互聯········ 11
2.2.3 RPV-FTGTI 算法········· 12
2.2.4 編隊內目標航跡的確認········ 18
2.2.5 編隊目標狀態矩陣的建立········ 19
2.2.6 仿真比較與分析·········· 20
2.2.7 討論··········· 34
2.3 集中式多傳感器編隊目標灰色航跡起始算法······ 35
2.3.1 多傳感器編隊目標航跡起始框架······ 35
2.3.2 多傳感器預互聯編隊內雜波的剔除······ 36
2.3.3 多傳感器編隊內量測合并模型······ 37
2.3.4 航跡得分模型的建立········ 38
2.4 基于運動狀態的集中式多傳感器編隊目標航跡起始算法····40
多傳感器編隊目標跟蹤
·VIII·
2.4.1 同狀態航跡子編隊獲取模型········ 40
2.4.2 多傳感器同狀態編隊關聯模型······ 45
2.4.3 編隊內航跡精確關聯合并模型······ 45
2.5 仿真比較與分析··········· 46
2.5.1 仿真環境··········· 47
2.5.2 仿真結果及分析·········· 47
2.6 本章小結············· 54
第3章 復雜背景下集中式多傳感器編隊目標跟蹤算法····· 56
3.1 引言············· 56
3.2 系統描述············· 56
3.3 云雨雜波和帶狀干擾剔除模型········· 57
3.3.1 云雨雜波剔除模型·········· 58
3.3.2 帶狀干擾剔除模型·········· 60
3.3.3 驗證分析··········· 61
3.4 基于模板匹配的集中式多傳感器編隊目標跟蹤算法····· 63
3.4.1 基于編隊整體的預互聯········ 63
3.4.2 模板匹配模型的建立········ 65
3.4.3 編隊內航跡的狀態更新········ 69
3.4.4 討論··········· 69
3.5 基于形狀方位描述符的集中式多傳感器編隊目標粒子濾波算法··· 69
3.5.1 編隊目標形狀矢量的建立········ 70
3.5.2 相似度模型的建立·········· 72
3.5.3 冗余圖像的剔除·········· 74
3.5.4 基于粒子濾波的狀態更新········ 74
3.6 仿真比較與分析··········· 75
3.6.1 仿真環境··········· 75
3.6.2 仿真結果··········· 76
3.6.3 仿真分析··········· 78
3.7 本章小結············· 79
第4章 集中式多傳感器機動編隊目標跟蹤算法····· 81
4.1 引言············· 81
4.2 典型機動編隊目標跟蹤模型的建立······· 82
目 錄
·IX·
4.2.1 編隊整體機動跟蹤模型的建立······ 82
4.2.2 編隊分裂跟蹤模型的建立········ 85
4.2.3 編隊合并跟蹤模型的建立········ 87
4.2.4 編隊分散跟蹤模型的建立········ 89
4.3 變結構JPDA機動編隊目標跟蹤算法······· 91
4.3.1 事件的定義··········· 92
4.3.2 編隊確認矩陣的建立········ 93
4.3.3 編隊互聯矩陣的建立········ 93
4.3.4 編隊確認矩陣的拆分········ 95
4.3.5 概率的計算··········· 97
4.3.6 編隊內航跡的狀態更新········ 100
4.4 擴展廣義S-維分配機動編隊目標跟蹤算法······ 101
4.4.1 基本模型的建立·········· 102
4.4.2 編隊量測的劃分·········· 103
4.4.3 3-維分配問題的構造········· 106
4.4.4 廣義S-維分配問題的構造········ 107
4.4.5 編隊內航跡的狀態更新········ 107
4.5 仿真比較與分析··········· 108
4.5.1 仿真環境··········· 108
4.5.2 仿真結果··········· 110
4.5.3 仿真分析··········· 113
4.6 本章小結············· 114
第5章 系統誤差下編隊目標航跡關聯算法······ 116
5.1 引言············· 116
5.2 系統誤差下基于雙重模糊拓撲的編隊目標航跡關聯算法··· 116
5.2.1 基于循環閾值模型的編隊航跡識別······ 117
5.2.2 第一重模糊拓撲關聯模型········ 118
5.2.3 第二重模糊拓撲關聯模型········ 123
5.3 系統誤差下基于誤差補償的編隊目標航跡關聯算法····· 125
5.3.1 編隊航跡狀態識別模型········ 125
5.3.2 編隊航跡系統誤差估計模型········ 127
5.3.3 誤差補償和編隊內航跡的精確關聯······ 130
5.3.4 討論··········· 130
多傳感器編隊目標跟蹤
·X·
5.4 仿真比較與分析··········· 131
5.4.1 仿真環境··········· 131
5.4.2 仿真結果及分析·········· 132
5.5 本章小結············· 134
第6章 結論及展望·········· 135
附錄A 式(2-17)中閾值參數ε 的推導······· 140
附錄B 式(5-19)的推導··········· 144
參考文獻·············· 148
CONTENTS
Chapter 1 Introduction············ 1
1.1 Background of Research········· 1
1.2 Internal and Oversea Research Actualities ······· 2
1.2.1 Track Initiation ·········· 2
1.2.2 Track Maintenance ·········· 3
1.2.3 Maneuvering Tracking ········ 3
1.3 The Key Problem to Be Resolved in Multi-sensor Formation Targets
Tracking Technique ············ 4
1.3.1 Formation Targets Track Initiation Technique with Clutter·· 4
1.3.2 Centralized Multi-sensor Formation Targets Tracking Technique
with the Complicated Background ········ 5
1.3.3 Centralized Multi-sensor Maneuvering Formation Targets Tracking
Technique ············· 5
1.3.4 Track Correlation Technique of the Formation Targets with
Systematic Errors ··········· 6
1.4 Main Content and Arragement of Dissertation····· 7
Chapter 2 Formation Targets Track Initiation Algorithm ····· 8
2.1 Introduction··········· 8
2.2 Formation Targets Gray Track Initiation Algorithm Based on Relative
Position Vector·············· 8
2.2.1 Preparative Division of the Formation Targets Based on the
Circulatory Threshold Model········· 10
2.2.2 Preparative Association Based on the Formation Center·· 11
2.2.3 RPV-FTGTI Algorithm ········· 12
2.2.4 Validation of the Tracks in the Formation····· 18
2.2.5 Establishment of the Formation Target State Matrix ···· 19
2.2.6 Simulation Comparision and Analysis······ 20
2.2.7 Discussion ··········· 34
2.3 Centralized Multi-sensor Formation Targets Gray Track Initiation
Algorithm ············· 35
2.3.1 Multi-sensor Formation Targets Track Initiation Frame ··· 35
2.3.2 Multi-sensor Clutter Deletion in Preparative Associated
多傳感器編隊目標跟蹤
·XII·
Formations ············· 36
2.3.3 Multi-sensor Measurement Mergence Model in the Formation · 37
2.3.4 Establishment of the Track Score Model ······ 38
2.4 Centralized Multi-sensor Formation Targets Track Initiation Algorithm
Based on Moving State··········· 40
2.4.1 Same-state Track SubFormation Obtainment Model···· 40
2.4.2 Multi-sensor Same-state Formation Association Model··· 45
2.4.3 Accurate Association and Mergence Model of the Formation
Tracks············· 45
2.5 Simulation Comparision and Analysis········ 46
2.5.1 Simulation Envirenment········· 47
2.5.2 Simulation Results and Analysis ······ 47
2.6 Summary············· 54
Chapter 3 Centralized Multi-sensor Formation Targets Tracking Algorithm with the
Complicated Background ··········· 56
3.1 Introduction··········· 56
3.2 System Description ··········· 56
3.3 Deletion Models of the Cloud-rain Clutter and the Narrow-Band
Interference············· 57
3.3.1 Cloud-rain Clutter Deletion Model ······ 58
3.3.2 Narrow-Band Interference Deletion Model ····· 60
3.3.3 Validation and Analysis ········ 61
3.4 Centralized Multi-sensor Formation Targets Tracking Algorithm Based on
Template Matching············· 63
3.4.1 Preparative Association Based on the Whole Formation ··· 63
3.4.2 Establishment of the Template Matching Model ····· 65
3.4.3 State Update of the Tracks in the Formation···· 69
3.4.4 Discussion··········· 69
3.5 Centralized Multi-sensor Formation Targets Particle Filter Based on Shape
and Azimuth Descriptor············ 69
3.5.1 Establishment of the Formation Targets Shape Vector··· 70
3.5.2 Establishment of the Resemble Model····· 72
3.5.3 Deletion of the Redundant Picture ······· 74
3.5.4 State Update Based on Particle Filter······· 74
CONTENTS
·XIII·
3.6 Simulation Comparision and Analysis········ 75
3.6.1 Simulation Envirenment········· 75
3.6.2 Simulation Results·········· 76
3.6.3 Simulation Analysis·········· 78
3.7 Summary············· 79
Chapter 4 Centralized Multi-sensor Maneuvering Formation Targets Tracking
Algorithm ············· 81
4.1 Introduction··········· 81
4.2 Establishment of Typical Maneuvering Formation Targets Tracking
Models ·············· 82
4.2.1 Establishment of the Formation Whole Maneuver Tracking
Model ············· 82
4.2.2 Establishment of the Formation Splitting Tracking Model·· 85
4.2.3 Establishment of the Formation merging Tracking Model ·· 87
4.2.4 Establishment of the Formation dispersing Tracking Model ··· 89
4.3 Maneuvering Formation Targets Tracking Algorithm Based on Different
Structure JPDA Technique············ 91
4.3.1 Event Definition ········· 92
4.3.2 Establishment of the Formation Validation Matrix ···· 93
4.3.3 Establishment of the Formation Association Matrix···· 93
4.3.4 Splitting of the Formation Validation Matrix ····· 95
4.3.5 Calculation of the Probability······· 97
4.3.6 State Update of the Tracks in the Formation···· 100
4.4 Maneuvering Formation Targets Tracking Algorithm Based on Patulous
Generalized S-D Assignment Technique········ 101
4.4.1 Establishment of the Basic Model······ 102
4.4.2 Partition of the Measurements of the Formation Targets ··· 103
4.4.3 Conformation of 3-D Assignment Problem ····· 106
4.4.4 Conformation of Generalized S-D Assignment Problem ··· 107
4.4.5 State Update of the Tracks in the Formation···· 107
4.5 Simulation Comparision and Analysis······ 108
4.5.1 Simulation Envirenment········· 108
4.5.2 Simulation Results·········· 110
4.5.3 Simulation Analysis········ 113
多傳感器編隊目標跟蹤
·XIV·
4.6 Summary··········· 114
Chapter 5 Formation Targets Track Correlation Algorithm with Systematic
Errors ···············116
5.1 Introduction··········· 116
5.2 Formation Targets Track Correlation Algorithm with Systematic Errors
Based on Double Fussy Topology·········· 116
5.2.1 Formation Tracks Identification Based on Circulatory Threshold
Model ············· 117
5.2.2 The First Scale Fussy Topology Model······ 118
5.2.3 The Second Scale Fussy Topology Model ····· 123
5.3 Formation Targets Track Correlation Algorithm with Systematic Errors
Based on Error Compensation·········· 125
5.3.1 Formation Track State Identification Model ···· 125
5.3.2 Formation Track Systematic Error Estimation Model ··· 127
5.3.3 Error Compensation and Formation Track Accurate
Correlation ············· 130
5.3.4 Discussion··········· 130
5.4 Simulation Comparision and Analysis······ 131
5.4.1 Simulation Envirenment········· 131
5.4.2 Simulation Results and Analysis ······ 132
5.5 Summary··········· 134
Chapter 6 Conclusions and Prospects ········ 135
Appendix A Illation of the Threshold Parameter ε in Formula (2-17) ·· 140
Appendix B Illation of Formula (5-19)······· 144
References············ 148 |
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