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              基于改進艦尾流模型和多層耦合分析的機載雷達測量建模

              葛泉波 王遠亮 李宏

              葛泉波, 王遠亮, 李宏. 基于改進艦尾流模型和多層耦合分析的機載雷達測量建模. 自動化學報, 2024, 50(3): 617?639 doi: 10.16383/j.aas.c220815
              引用本文: 葛泉波, 王遠亮, 李宏. 基于改進艦尾流模型和多層耦合分析的機載雷達測量建模. 自動化學報, 2024, 50(3): 617?639 doi: 10.16383/j.aas.c220815
              Ge Quan-Bo, Wang Yuan-Liang, Li Hong. Airborne radar measurement modeling based on improved carrier air wake model and multi-layer coupling analysis. Acta Automatica Sinica, 2024, 50(3): 617?639 doi: 10.16383/j.aas.c220815
              Citation: Ge Quan-Bo, Wang Yuan-Liang, Li Hong. Airborne radar measurement modeling based on improved carrier air wake model and multi-layer coupling analysis. Acta Automatica Sinica, 2024, 50(3): 617?639 doi: 10.16383/j.aas.c220815

              基于改進艦尾流模型和多層耦合分析的機載雷達測量建模

              doi: 10.16383/j.aas.c220815
              基金項目: 國家自然科學基金(62033010, U23B2061), 江蘇省“青藍工程” (R2023Q07)資助
              詳細信息
                作者簡介:

                葛泉波:南京信息工程大學教授. 主要研究方向為狀態估計與信息融合, 自主智能無人系統, 飛行器測試數據分析和電力物聯網技術. 本文通信作者. E-mail: 003535@nuist.edu.cn

                王遠亮:上海海事大學物流工程學院博士研究生. 2020年獲天津理工大學電氣電子工程學院碩士學位. 主要研究方向為無人艦載機位姿估計, 卡爾曼濾波算法的應用. E-mail: 202040210002@stu.shmtu.edu.cn

                李宏:中國飛行試驗研究院研究員. 主要研究方向為航空飛行器測試, 光電測量, 試驗數據處理, 系統工程設計. E-mail: lihongcfte@163.com

              • 中圖分類號: Y

              Airborne Radar Measurement Modeling Based on Improved Carrier Air Wake Model and Multi-layer Coupling Analysis

              Funds: Supported by National Natural Science Foundation of China (62033010, U23B2061) and Qing Lan Project of Jiangsu Province (R2023Q07)
              More Information
                Author Bio:

                GE Quan-Bo Professor at Nanjing University of Information Science and Technology. His research interest covers state estimation and information fusion, autonomous intelligent unmanned system, aircraft test data analysis, and power internet of things technology. Corresponding author of this paper

                WANG Yuan-Liang Ph.D. candidate at the Logistics Engineering College, Shanghai Maritime University. He received his master degree from the College of Electronic Engineering, Tianjin University of Technology in 2020. His research interest covers UCA pose estimation and application of Kalman filter algorithm

                LI Hong Researcher at Chinese Flight Test Establishment. His research interest covers aircraft test, photoelectric measurement, test data processing, and system engineering design

              • 摘要: 為提高復雜海洋環境中無人艦載機(Unmanned carrier-based aircraft, UCA)自動著艦時導航定位的準確性, 研究艦尾流對機載雷達測量過程的動態影響問題, 建立一種基于多層級耦合性分析的測量影響動態建模分析方法. 首先, 利用直接分解法和前向差分法建立一種基于離散化狀態空間的時變艦尾流模型, 以克服傳統傳遞函數方法存在的局限性; 其次, 基于艦尾流各分量均與飛機飛行速度相關的客觀事實, 通過在時變系統中考慮艦尾流分量間的相互作用關系來構建一種更符合實際系統特征的分量自耦合艦尾流模型; 緊接著, 采用UCA姿態角變化能夠改變坐標轉換矩陣的思想, 研究艦尾流與UCA位姿變化間的耦合聯系, 提出一種準確性更高的艦尾流對UCA位姿的深度影響模型; 然后, 以航母姿態變化對艦載雷達測量結果的影響模型為基礎, 通過考慮本研究場景的內在特性, 建立UCA姿態變化對雷達測量結果的影響模型分析方法; 緊接著, 采用示意圖方式獲得位移變化對機載雷達測量結果的影響模型; 最后, 針對艦船受海洋大氣(風、浪、流)干擾而出現失速這一現象, 建立實際海洋環境中艦尾流對機載雷達測量結果的非線性非高斯影響分析模型. 仿真實驗研究驗證了上述模型分析方法的有效性和優越性.
              • 圖  1  研究思路框圖

                Fig.  1  Block diagram of research ideas

                圖  2  自耦合存在性示意圖

                Fig.  2  Self coupling existence diagram

                圖  3  航母姿態角對應無人機姿態角示意圖

                Fig.  3  Schematic diagram of UCA attitude angle corresponding to aircraft carrier attitude angle

                圖  4  不同平臺中雷達所處位置坐標示意圖

                Fig.  4  Schematic diagram of radar position coordinates in different platforms

                圖  5  由橫滾角和俯仰角導致的方位角影響

                Fig.  5  Azimuth angle error caused by roll and pitch angle

                圖  6  姿態變化對傳感器測量的距離影響示意圖

                Fig.  6  Schematic diagram of the influence of attitude change on the distance measured by the sensor

                圖  7  UCA位置確定示意圖和位置變化示意圖

                Fig.  7  UCA location determination diagram and location change diagram

                圖  8  沿Z軸、Y軸和X軸運動的測量影響示意圖

                Fig.  8  Schematic diagram of measurement effects along Z-axis, Y-axis and X-axis movements

                圖  9  大氣紊流狀態空間模型三個方向風速對比圖

                Fig.  9  Comparison of wind speeds in three directions of the spatial model of atmospheric turbulence states

                圖  10  隨機分量狀態空間模型三個方向風速對比圖

                Fig.  10  Comparison plot of wind speeds in three directions of the stochastic component state space model

                圖  11  不同艦尾流模型三個方向風速對比圖

                Fig.  11  Comparison chart of wind speeds in three directions for different carrier air wake models

                圖  12  不同艦尾流模型三個方向風速誤差對比圖

                Fig.  12  Comparison of wind speed errors in three directions of different carrier air wake models

                圖  13  慣性坐標系三軸方向的位移變化模型

                Fig.  13  Displacement variation model in three-axis direction in inertial coordinate system

                圖  14  慣性坐標系三軸方向的位移變化誤差對比圖

                Fig.  14  Comparison plot of displacement change error in the triaxial direction of the inertial coordinate system

                圖  15  UCA姿態角變化模型

                Fig.  15  UCA attitude angle change model

                圖  16  UCA姿態角變化誤差對比

                Fig.  16  Comparison of UCA attitude angle change error

                圖  17  位移變化對機載雷達測量結果的影響仿真對比圖

                Fig.  17  Simulation comparison diagram of the influence of displacement change on the measurement accuracy of airborne radar

                圖  18  位移變化對雷達測量結果的影響誤差仿真對比圖

                Fig.  18  Error simulation comparison diagram of influence of displacement change on radar measurement accuracy

                圖  19  姿態變化對雷達測量結果的影響仿真對比圖

                Fig.  19  Simulation comparison diagram of the influence of attitude change on radar measurement accuracy

                圖  20  姿態變化對雷達測量結果的影響誤差仿真對比圖

                Fig.  20  Error simulation comparison diagram of influence of attitude change on airborne radar measurement accuracy

                圖  21  位姿變化對機載雷達測量結果的影響仿真對比圖

                Fig.  21  Simulation comparison diagram of the influence of position and attitude changes on the measurement accuracy of airborne radar

                圖  22  位姿變化對雷達測量結果的影響誤差仿真對比圖

                Fig.  22  Error simulation comparison diagram of influence of position and attitude change on airborne radar measurement accuracy

                圖  23  艦尾流對雷達測量結果影響的非高斯性驗證

                Fig.  23  Verification of non-Gaussian effect of ship wake on radar measurement accuracy

                圖  24  風速誤差對比圖

                Fig.  24  Comparison diagram of wind speed error

                圖  25  兩種模型對雷達測量結果影響的誤差仿真對比圖

                Fig.  25  Error simulation comparison diagram of the influence of two models on radar measurement results

                表  1  三種模型均方根誤差結果

                Table  1  Root mean square error results of three models

                TCAWACAWCCAW
                $u_g\text{-}{\rm{RMSE}} $0.47910.30360.2979
                $l_g\text{-}{\rm{RMSE}} $0.24810.20250.1951
                $w_g\text{-}{\rm{RMSE}} $0.71800.39600.3918
                下載: 導出CSV

                表  2  兩種位移變化模型均方根誤差結果

                Table  2  Root mean square error results of two displacement variation models

                DTCAWDCCAW
                dx-RMSE0.04420.0240
                dy-RMSE0.06610.0410
                dz-RMSE0.03930.0218
                下載: 導出CSV

                表  3  兩種姿態變化模型均方根誤差結果

                Table  3  Root mean square error results of two attitude change models

                ATCAWACCAW
                ${\rm{d}}\theta$-RMSE0.01440.0079
                ${\rm{d}}\psi$-RMSE0.00500.0040
                ${\rm{d}}\phi$-RMSE0.07200.0397
                下載: 導出CSV

                表  4  兩種位移變化干擾下測量影響模型均方根誤差結果

                Table  4  Root mean square error results of measurement influence model under two kinds of displacement changes

                RDTCAWRDCCAW
                dR-RMSE0.06640.0356
                dE-RMSE5.5629 × 10?42.6464 × 10?4
                dA-RMSE8.2381 × 10?42.6558 × 10?4
                下載: 導出CSV

                表  5  兩種姿態變化干擾下測量影響模型均方根誤差結果

                Table  5  Root mean square error results of measurement influence model under two kinds of attitude changes

                RATCAWRACCAW
                ${\rm{d}}R$-RMSE0.02130.0130
                ${\rm{d}}E$-RMSE0.04360.0276
                ${\rm{d}}A$-RMSE0.41170.2321
                下載: 導出CSV

                表  6  兩種位姿變化干擾下測量影響模型均方根誤差結果

                Table  6  Root mean square error results of measurement influence model under the interference of two kinds of posture changes

                RPTCAWRPCCAW
                ${\rm{d}}R$-RMSE0.07450.0347
                ${\rm{d}}E$-RMSE0.04360.0277
                ${\rm{d}}A$-RMSE0.41170.2321
                下載: 導出CSV

                表  7  兩種風速模型均方根誤差結果

                Table  7  Root mean square error results of two wind speed models

                CCAWSCCAW
                $u_g\text{-}{\rm{RMSE}} $0.25600.2260
                $l_g\text{-}{\rm{RMSE}} $0.22610.1905
                $w_g\text{-}{\rm{RMSE}} $0.33160.3143
                下載: 導出CSV

                表  8  兩種測量影響模型均方根誤差結果

                Table  8  Root mean square error results of two measurement impact models

                RPCCAWWRPCCAW
                ${\rm{d}}R$-RMSE0.04520.0379
                ${\rm{d}}E$-RMSE0.05470.0504
                ${\rm{d}}A$-RMSE0.67780.6772
                下載: 導出CSV
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                      1. [1] Ahmed R F, Golam Kibria B M. Robust ground moving target detection for airborne radar using a novel feature-based machine learning approach. Journal of the Franklin Institute, 2022, 359(9): 4449-4467 doi: 10.1016/j.jfranklin.2022.04.031
                        [2] Chen H M, Lu Y B, Liu J, Yi X L, Sun H W, Mu H Q, et al. Efficient knowledge-aided target relocation algorithm for airborne radar. The Journal of Engineering, 2019, 2019(21): 7589-7592 doi: 10.1049/joe.2019.0642
                        [3] Kang X J, Li J, Fan X T, Wan W H. Real-time RGB-D simultaneous localization and mapping guided by terrestrial LiDAR point cloud for indoor 3-D reconstruction and camera pose estimation. Applied Sciences, 2019, 9(16): Article No. 3264 doi: 10.3390/app9163264
                        [4] Chen L L, Lv Z Y, Shen X Y, Wu Y H, Sun X M. Adaptive attitude control for a coaxial tilt-rotor UAV via immersion and invariance methodology. IEEE/CAA Journal of Automatica Sinica, 2022, 9(9): 1710-1713 doi: 10.1109/JAS.2022.105827
                        [5] 王峰, 黃子路, 韓孟臣, 邢立寧, 王凌. 基于KnCMPSO算法的異構無人機協同多任務分配. 自動化學報, 2023, 49(2): 399-414

                        Wang Feng, Huang Zi-Lu, Han Meng-Chen, Xing Li-Ning, Wang Ling. A knee point based coevolution multi-objective particle swarm optimization algorithm for heterogeneous UAV cooperative multi-task allocation. Acta Automatica Sinica, 2023, 449(2): 399-414
                        [6] 楊智博. 艦載機自動著艦系統縱向控制策略研究 [博士學位論文], 哈爾濱工程大學, 中國, 2020.

                        Yang Zhi-Bo. Research on Longitudinal Control Strategy of the Automatic Carrier Landing System [Ph.D. dissertation], Harbin Engineering University, China, 2020.
                        [7] Li X, Duan H B, Tian Y L, Wang F Y. Exploring image generation for UAV change detection. IEEE/CAA Journal of Automatica Sinica, 2022, 9(6): 1061-1072 doi: 10.1109/JAS.2022.105629
                        [8] 范云生, 陳欣宇, 趙永生, 宋保健. 基于擴張狀態觀測器的四旋翼吊掛飛行系統非線性控制. 自動化學報, 2023, 49(8): 1758-1770

                        Fan Yun-Sheng, Chen Xin-Yu, Zhao Yong-Sheng, Song Bao-Jian. Nonlinear control of quadrotor suspension system based on extended state observer. Acta Automatica Sinica, 2023, 49(8): 1758-1770
                        [9] 王鑫. 飛翼布局無人機自主著艦控制關鍵技術研究 [博士學位論文], 南京航空航天大學, 中國, 2017.

                        Wang Xin. Technology of Automatic Carrier Landing for Flying-Wing Unmanned Aerial Vehichle [Ph.D. dissertation], Nanjing University of Aeronautics and Astronautics, China, 2017.
                        [10] Hao R Z, Huang J. On construction method of shipborne and airborne radar intelligence and related equipment knowledge graph. Journal of Physics: Conference Series, 2017, 887: Article No. 012042
                        [11] 譚文淵, 曹義華. 基于嵌套網格的艦載直升機流場仿真及風限圖計算. 航空動力學報, 2020, 35(10): 2166-2175

                        Tan Wen-Yuan, Cao Yi-Hua. Simulation of flow field and calculation of safe operating envelope of shipborne helicopter based on chimera grid. Journal of Aerospace Power, 2020, 35(10): 2166-2175
                        [12] Department of Defense Handbook. Flying Qualities of Piloted Aircraft, MIL-HDBK-1797, 1997.
                        [13] 趙所, 李震, 侯中喜, 張大為. 艦尾流場擾動影響分析及抑制技術研究. 華中科技大學學報(自然科學版), 2021, 49(6): 86-91

                        Zhao Suo, Li Zhen, Hou Zhong-Xi, Zhang Da-Wei. Study on influence analysis and rejection technology of carrier air wake. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2021, 49(6): 86-91
                        [14] 陶楊, 韓維. 基于改進多目標遺傳算法的艦尾紊流模擬方法. 北京航空航天大學學報, 2015, 41(3): 443-448

                        Tao Yang, Han Wei. Carrier airwake simulation methods based on improved multi-objective genetic algorithm. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(3): 443-448
                        [15] 羅飛, 張軍紅, 王博, 唐瑞琳, 唐煒. 基于直接升力與動態逆的艦尾流抑制方法. 航空學報, 2021, 42(12): 187-202

                        Luo Fei, Zhang Jun-Hong, Wang Bo, Tang Rui-Lin, Tang Wei. Air wake suppression method based on direct lift and nonlinear dynamic inversion control. Acta Aeronautica et Astronautica Sinica, 2021, 42(12): 187-202
                        [16] 周俊. 艦載機著艦飛/推綜合控制技術研究 [碩士學位論文], 南京航空航天大學, 中國, 2018.

                        Zhou Jun. Research on Carrier Aircraft Landing Based on Integrated Filght/Propulsion Control [Master thesis], Nanjing University of Aeronautics and Astronautics, China, 2018.
                        [17] 賁亮亮. 艦載機著艦環境擾動影響及其響應分析 [碩士學位論文], 南京航空航天大學, 中國, 2013.

                        Ben Liang-Liang. The Environmental Disturbance Influence and Response Analysis on Approaching of Shipboard Aircraft [Master thesis], Nanjing University of Aeronautics and Astronautics, China, 2013.
                        [18] 周志恒, 趙建軍, 桑德一, 楊利斌. 艦艇姿態對作戰系統動態對準精度的影響分析. 兵工自動化, 2016, 35(5): 51-55, 71

                        Zhou Zhi-Heng, Zhao Jian-Jun, Sang De-Yi, Yang Li-Bin. Analysis of effects on alignment in dynamic state precision of warship combat system caused by its attitude. Ordnance Industry Automation, 2016, 35(5): 51-55, 71
                        [19] 桑德一, 趙建軍, 楊利斌. 航母運動對著艦引導雷達精度的影響. 中國艦船研究, 2014, 9(6): 8-13 doi: 10.3969/j.issn.1673-3185.2014.06.002

                        Sang De-Yi, Zhao Jian-Jun, Yang Li-Bin. The impact on landing guidance radar precision caused by the movement of aircraft carriers. Chinese Journal of Ship Research, 2014, 9(6): 8-13 doi: 10.3969/j.issn.1673-3185.2014.06.002
                        [20] 王可, 徐明亮, 李亞飛, 姜曉恒, 魯愛國, 李鑒. 一種面向航空母艦甲板運動狀態預估的魯棒學習模型. 自動化學報, DOI: 10.16383/j.aas.c210664

                        Wang Ke, Xu Ming-Liang, Li Ya-Fei, Jiang Xiao-Heng, Lu Ai-Guo, Li Jian. A robust learning model for deck motion prediction of aircraft carrier. Acta Automatica Sinica, DOI: 10.16383/j.aas.c210664
                        [21] Wang Y L, Li H, Ge Q B. A novel modeling analysis of carrier air wake based on component coupling correlation. In: Proceedings of the IEEE International Conference on Unmanned Systems (ICUS). Beijing, China: IEEE, 2021. 970?975
                        [22] 肖業倫, 金長江. 大氣擾動中的飛行原理. 北京: 國防工業出版社, 1993.

                        Xiao Ye-Lun, Jin Chang-Jiang. Flight Principle in Atmospheric Disturbance. Beijing: National Defense Industry Press, 1993.
                        [23] Jiao X, Jiang J, Wang X H, Zhen Z Y. Research on effects of sea states on air wake. In: Proceedings of the 6th IEEE Conference on Industrial Electronics and Applications. Beijing, China: IEEE, 2011. 758?762
                        [24] 李新飛. 艦載機起降關鍵技術仿真研究 [博士學位論文], 哈爾濱工程大學, 中國, 2012.

                        Li Xin-Fei. Simulation of Key Technology of Lanuch and Land for Carrier-Based Aircraft [Ph.D. dissertation], Harbin Engineering University, China, 2012.
                        [25] Cui K K, Han W, Liu Y J, Wang X W, Su X C, Liu J. Model predictive control for automatic carrier landing with time delay. International Journal of Aerospace Engineering, 2021, 2021: Article No. 8613498
                        [26] Zhu Q D, Yang Z B. Design of air-wake rejection control for longitudinal automatic carrier landing cyber-physical system. Computers & Electrical Engineering, 2020, 84: Article No. 106637
                        [27] 牟杭. 多輸入多輸出振動系統狀態空間建模方法研究 [碩士學位論文], 南京航空航天大學, 中國, 2018.

                        Mou Hang. Research on State Space Modeling Method for Multi-Input and Multi-Output Vibration System [Master thesis], Nanjing University of Aeronautics and Astronautics, China, 2018.
                        [28] Nagrath J, Goral M. Control System Engineering. Hoboken: Wiley Eastern Limited, 2016.
                        [29] 謝莉, 楊慧中, 丁鋒. 非均勻采樣數據系統的新型模型描述方法. 自動化學報, 2017, 43(5): 806-813

                        Xie Li, Yang Hui-Zhong, Ding Feng. Novel input-output representation of non-uniformly sampled-data systems. Acta Automatica Sinica, 2017, 43(5): 806-813
                        [30] 劉文定. 自動控制原理. 第4版. 北京: 電子工業出版社, 2018.

                        Liu Wen-Ding. Automatic Control Principle (4th edition). Beijing: Electronic Industry Press, 2018.
                        [31] 胡壽松. 自動控制原理. 第7版. 北京: 科學出版社, 2019.

                        Hu Shou-Song. Automatic Control Principle (Seventh edition). Beijing: Science Press, 2019.
                        [32] 劉豹, 唐萬生. 現代控制理論. 北京: 機械工業出版社, 2017.

                        Liu Bao, Tang Wan-Sheng. Modern Control Theory. Beijing: China Machine Press, 2017.
                        [33] 段廣仁. 高階系統方法-II. 能控性與全驅性. 自動化學報, 2020, 46(8): 1571-1581

                        Duan Guang-Ren. High-order system approaches: Ⅱ. Controllability and full-actuation. Acta automatica Sinica, 2020, 46(8): 1571-1581
                        [34] Li W, Zhao S X, Liu K, Lu H C, Fan T H. Dynamic response calculation algorithm for floating offshore wind turbines based on a state-space method of transfer function. Frontiers in Energy Research, 2022, 10: 909416 doi: 10.3389/fenrg.2022.909416
                        [35] 田玉平. 自動控制原理. 北京: 科學出版社, 2018.

                        Tian Yu-Ping. Automatic Control Principle. Beijing: Science Press, 2018.
                        [36] Bartecki K. Approximate state-space and transfer function models for 2@2 linear hyperbolic systems with collocated boundary inputs. International Journal of Applied Mathematics and Computer Science, 2020, 30(3): 475-491
                        [37] 李繁飆, 楊皓月, 王鴻鑫, 陽春華, 廖力清. 基于干擾估計的非對稱運動下飛機剎車系統模型預測控制. 自動化學報, 2022, 48(7): 1690-1703

                        Li Fan-Biao, Yang Hao-Yue, Wang Hong-Xin, Yang Chun-Hua, Liao Li-Qing. Model predictive control of aircraft braking system under asymmetric motion based on disturbance estimation. Acta Automatica Sinica, 2022, 48(7): 1690-1703
                        [38] 李繁飆, 黃培銘, 陽春華, 廖力清, 桂衛華. 基于非線性干擾觀測器的飛機全電剎車系統滑??刂圃O計. 自動化學報, 2021, 47(11): 2557-2569

                        Li Fan-Biao, Huang Pei-Ming, Yang Chun-Hua, Liao Li-Qing, Gui Wei-Hua. Sliding mode control design of aircraft electric brake system based on nonlinear disturbance observer. Acta Automatica Sinica, 2021, 47(11): 2557-2569
                        [39] 孫榮恒. 應用數理統計. 第3版. 北京: 科學出版社, 2014.

                        Sun Rong-Heng. Applied Mathematical Statistics (3rd edition). Beijing: Science Press, 2014.
                        [40] 李永泉, 郭雨, 張陽, 張立杰. 基于牛頓歐拉法的一種空間被動過約束并聯機構動力學建模方法. 機械工程學報, 2020, 56(11): 48-57 doi: 10.3901/JME.2020.11.048

                        Li Yong-Quan, Guo Yu, Zhang Yang, Zhang Li-Jie. Dynamic modeling method of spatial passive over-constrained parallel mechanism based on newton Euler method. Journal of Mechanical Engineering, 2020, 56(11): 48-57 doi: 10.3901/JME.2020.11.048
                        [41] 謝新連, 王余寬, 何傲, 潘偉, 許小衛. 考慮風浪流影響的船舶路徑規劃及算法. 重慶交通大學學報(自然科學版), 2022, 41(7): 1-8

                        Xie Xin-Lian, Wang Yu-Kuan, He Ao, Pan Wei, Xu Xiao-Wei. Ship path planning and algorithm considering the effect of wind, wave and current. Journal of Chongqing Jiaotong University (Natural Science), 2022, 41(7): 1-8
                        [42] 魏照坤. 風浪影響下的集裝箱船舶航速優化 [博士學位論文], 大連海事大學, 中國, 2018.

                        Wei Zhao-Kun. The Containerships Sailing Speed Optimization Considering Wind and Waves [Ph.D. dissertation], Dalian Maritime University, China, 2018.
                        [43] 國強, 李文韜. 基于正則化約束總體最小二乘的TDOA/FDOA無源定位方法. 哈爾濱工業大學學報, 2022, 54(5): 81-87

                        Guo Qiang, Li Wen-Tao. Passive TDOA/FDOA location based on regularized constrained total least squares. Journal of Harbin Institute of Technology, 2022, 54(5): 81-87
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                        出版歷程
                        • 收稿日期:  2022-10-16
                        • 錄用日期:  2023-02-23
                        • 網絡出版日期:  2023-08-21
                        • 刊出日期:  2024-03-29

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