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Chinese Journal of Engineering Design  2024, Vol. 31 Issue (3): 332-339    DOI: 10.3785/j.issn.1006-754X.2024.03.209
Mechanical Optimization Design     
Analysis of radar detection distance and ranging accuracy based on subinterval
Heng OUYANG1,2(),Shuo GAO1,2,Shitao WANG3,Zhengyan MA1,2,Dequan ZHANG1,2()
1.School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China
2.State Key Lab of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300401, China
3.No. 31002 Troops, Beijing 100094, China
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Abstract  

Detection range and ranging accuracy are the key performance indicators of radar. Under actual service conditions, they are greatly affected by uncertain factors such as internal signal transmission loss and external signal interference of radar system. Improving its accuracy has become an important topic in the field of radar research. In order to evaluate the influence of the above uncertain factors on the radar performance, the uncertainty analysis of radar detection range and ranging accuracy was carried out. Firstly, the radar detection range and ranging accuracy models considering signal transmission loss and signal interference were established; secondly, the interval model was used to quantify the uncertainty parameters to realize the uncertainty measurement under the unified framework of internal and external parameters; then, the accurate response surface models of detection range and ranging accuracy were constructed, and the influence of multi-dimensional parameters on detection range and ranging accuracy was sorted by using Sobol' global sensitivity analysis method; finally, the subinterval decomposition analysis method was used to obtain the radar detection range and ranging accuracy range, and the results were compared with those calculated by Monte Carlo simulation method to verify the effectiveness of the proposed method. Reasonable tolerance and threshold values are set for radar detection range and ranging accuracy, which can improve the efficiency of radar performance analysis and reduce the cost of performance analysis.



Key wordsdetection distance      ranging accuracy      uncertainty      response surface      subinterval     
Received: 20 October 2023      Published: 27 June 2024
CLC:  TN 956  
Corresponding Authors: Dequan ZHANG     E-mail: ouyangheng@hebut.edu.cn;dequan.zhang@hebut.edu.cn
Cite this article:

Heng OUYANG,Shuo GAO,Shitao WANG,Zhengyan MA,Dequan ZHANG. Analysis of radar detection distance and ranging accuracy based on subinterval. Chinese Journal of Engineering Design, 2024, 31(3): 332-339.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2024.03.209     OR     https://www.zjujournals.com/gcsjxb/Y2024/V31/I3/332


基于子区间的雷达探测距离和测距精度分析

探测距离和测距精度是雷达的关键性能指标,在实际服役工况下受雷达系统内部信号传输损耗、外部信号干扰等不确定性因素的影响较大,提高其准确性已成为雷达研究领域的重要课题。为了评估上述不确定性因素对雷达性能的影响程度,开展了雷达探测距离和测距精度的不确定性分析。首先,建立了考虑信号传输损耗和信号干扰的雷达探测距离和测距精度模型;其次,采用区间模型量化不确定性参数,实现内外部参数统一框架下的不确定性度量;然后,构建准确的探测距离和测距精度响应面模型,并采用Sobol'全局敏感性分析方法实现多维参数对探测距离和测距精度影响的排序;最后,采用子区间分解分析方法获取了雷达探测距离和测距精度区间,并与通过蒙特卡洛模拟得到的结果进行对比,验证所提方法的有效性。将雷达探测距离和测距精度设定合理的容限与阈值,可提高雷达性能分析效率,降低性能分析成本。


关键词: 探测距离,  测距精度,  不确定性,  响应面,  子区间 
参数单位数值区间
信号频率108Hz[3.0, 10.0]
信号带宽105Hz[5.0, 10.0]
脉冲宽度10-3s[1.0, 2.0]
脉冲积累数[1, 10]
雷达发射功率105W[1.0, 5.0]
发射增益dB[35.0, 40.0]
接收增益dB[35.0, 40.0]
综合损耗dB[40.0, 45.0]
方位波束宽度(°)[2.0, 3.0]
俯仰波束宽度(°)[2.0, 3.0]
测角误差斜率[40.0, 70.0]
压制系数[40.0, 70.0]
干扰频率108Hz[3.0, 10.0]
干扰带宽Hz[3.0, 7.0]
干扰功率103W[3.0, 7.0]
干扰发射增益dB[10.0, 20.0]
Table 1 Radar parameters and interference parameters
Fig.1 Schematic of uncertain parameters affecting radar system performance
Fig.2 Local sensitivity analysis results of detection distance
Fig.3 Local sensitivity analysis results of ranging accuracy
模型R2ERMS
探测距离响应面模型0.997 00.000 3
测距精度响应面模型0.994 30.012 7
Table 2 Accuracy verification of response surface model of detection distance and ranging accuracy
影响参数单位数值区间敏感度
信号频率/干扰频率108 Hz[3.0, 10.0]0.449 7
脉冲宽度10-3 s[1.0, 2.0]0.035 8
雷达发射功率105 W[1.0, 5.0]0.174 1
发射增益dB[35.0, 40.0]0.104 3
接收增益dB[35.0, 40.0]0.111 1
综合损耗dB[40.0, 45.0]0.104 8
Table 3 Global sensitivity analysis results of detection range
影响参数单位数值区间敏感度
信号带宽105 Hz[5.0, 10.0]0.242 3
脉冲宽度10-3 s[1.0, 2.0]0.020 6
脉冲积累数[1, 10]0.404 1
发射增益dB[35.0, 40.0]0.070 4
接收增益dB[35.0, 40.0]0.071 0
压制系数dB[40.0, 70.0]0.013 0
Table 4 Global sensitivity analysis results of ranging accuracy
Fig.4 Analysis flowchart of radar detection distance and ranging accuracy
N探测距离区间测距精度区间
3[71 200, 167 124][3.60, 1 660.35]
4[167 385, 713 175][4.90,1 683.24]
5[167 385, 713 175][4.90, 1 683.24 ]
Table 5 Radar detection distance and ranging accuracy range under different subintervals
Table 6 Uncertainty analysis results of radar performance under different methods
[1]   保铮. “雷达信号处理”专刊序言[J].电子与信息学报,2016,38(12):2987. doi:10.3969/j.issn.1009-5896.2016.12.001
BAO Z. "Radar signal processing" special issue preface[J]. Journal of Electronics & Information Technology, 2016, 38(12): 2987.
doi: 10.3969/j.issn.1009-5896.2016.12.001
[2]   王晓海. 认知雷达系统技术发展综述[J].数字通信世界, 2018():40-43. doi:10.1109/icc.2018.8422762
WANG X H. Review on the development of cognitive radar systems[J]. Digital Communication World, 2018 (): 40-43.
doi: 10.1109/icc.2018.8422762
[3]   LI Y, ZHAO W. A correction method for radar detection range analysis in interference environment[C]//ITM Web of Conferences, León, Guanajuato, Oct. 5-7, 2022.
[4]   MAHAFZA B R. Radar systems analysis and design using matlab[M]. Boca Raton: CRC Press, 2021.
[5]   刘育才,马晓静,雷红. “本土链”雷达主要性能分析及启示[J].火控雷达技术,2022,51(4):47-52.
LIU Y C, MA X J, LEI H. The main performance analysis and enlightenment of the CH radar[J]. Fire Control Radar Technology, 2022, 51(4): 47-52.
[6]   DONG B, LI G, WANG K, et al. Range aliasing elimination for FMICW radar with uniform sampling bursts and poisson disk inter-burst delays[J]. IEEE Sensors Journal, 2022, 22(2): 1495-1508.
[7]   曹丽,宋梦洋,凌九红. 车载激光雷达关键性能参数及决定因素[J].汽车实用技术,2022,47(24):196-199. doi:10.16638/j.cnki.1671-7988.2022.024.036
CAO L, SONG M Y, LING J H. Key performance parameters and determinants of vehicle lidar[J]. Automobile Applied Technology, 2022, 47(24): 196-199.
doi: 10.16638/j.cnki.1671-7988.2022.024.036
[8]   CHANG H Y, CHEN Y Y, CHUNG W H. RangeSRN: range super-resolution network using mmwave FMCW radar[C]//2022 IEEE Global Communications Conference, Rio de Janeiro, Dec. 4-8, 2022.
[9]   李琴,黄卡玛. 低空小型无人机雷达探测距离仿真分析[J].无线电工程,2018,48(4):303-307. doi:10.3969/j.issn.1003-3106.2018.04.11
LI Q, HUANG K M. Simulation analysis of radar detection range for small low-altitude UAV[J]. Radio Engineering, 2018, 48(4): 303-307.
doi: 10.3969/j.issn.1003-3106.2018.04.11
[10]   ZHAO M X, ZHANG X, YANG Q, et al. Using sky-wave echoes information to extend HFSWR's maximum detection range[J]. Radio Science, 2018, 53(8): 922-932.
[11]   董云龙,刘洋,刘宁波,等. 基于雷达方程修正的目标探测距离评估方法[J].信号处理,2022,38(10):2102-2113.
DONG Y L, LIU Y, LIU N B, et al. A method for evaluating target detection range based on radar range equation modification[J]. Journal of Signal Processing, 2022, 38(10): 2102-2113.
[12]   汤华涛,察豪,田斌,等. 微波超视距雷达组网探测范围研究[J].电波科学学报,2022,37(2):274-278. doi:10.12265/j.cjors.2021114
TANG H T, CHA H, TIAN B, et al. Study on detection range of microwave over-the-horizon radar network[J]. Chinese Journal of Radio Science, 2022, 37(2): 274-278.
doi: 10.12265/j.cjors.2021114
[13]   陈超凡,江晶,李佳炜,等. 雷达实际探测威力快速生成算法研究[J].计算机仿真,2022,39(11):7-10,183. doi:10.3969/j.issn.1006-9348.2022.11.002
CHEN C F, JIANG J, LI J W, et al. Research on a fast generation algorithm of radar detection power[J]. Computer Simulation, 2022, 39(11): 7-10, 183.
doi: 10.3969/j.issn.1006-9348.2022.11.002
[14]   马兰,李照照,杨雪林,等. 基于高斯插值提高雷达测距精度的研究[J].火控雷达技术,2021,50(1):41-47.
MA L, LI Z Z, YANG X L, et al. Improving radar ranging accuracy based on Gaussian interpolation[J]. Fire Control Radar Technology, 2021, 50(1): 41-47.
[15]   MAROM H, BAR S Y, MILGROM B. Bistatic radar tracking with significantly improved bistatic range accuracy[J]. IEEE Transactions on Aerospace and Electronic Systems, 2023, 59(1): 52-62.
[16]   李鑫洋,王洪源. 提高FMCW雷达测距精度的算法研究[J].中国新技术新产品,2016(19):4-5. doi:10.3969/j.issn.1673-9957.2016.19.002
LI X Y, WANG H Y. Research on algorithm to improve the ranging accuracy of FMCW radar[J]. New Technology & New Products of China, 2016(19): 4-5.
doi: 10.3969/j.issn.1673-9957.2016.19.002
[17]   SIM J Y, YANG J R. Frequency discrimination method using asymmetric transmission time in FSK radar[J]. Journal of Electromagnetic Engineering and Science, 2022, 22(4): 496-501.
[18]   XU Z, QI S, ZHANG P. A coherent CZT-based algorithm for high-accuracy ranging with FMCW radar[J]. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-11.
[19]   罗韩君,周仁龙,张禹涛. 光子雷达探测性能与测距精度的理论研究[J].激光技术,2014,38(3):411-416. doi:10.7510/jgjs.issn.1001-3806.2014.03.028
LUO H J, ZHOU R L, ZHANG Y T. Theoretical analysis of detection performance and range accuracy of photon ladar[J]. Laser Technology, 2014, 38(3): 411-416.
doi: 10.7510/jgjs.issn.1001-3806.2014.03.028
[20]   李妍,陈超,程光权,等. 面向不确定性数据的雷达预警建模方法研究[J].郑州大学学报(理学版),2022,54(5): 37-42.
LI Y, CHEN C, CHENG G Q, et al. Research on radar warning modelling methods for uncertainty-oriented data[J]. Journal of Zhengzhou University (Natural Science Edition), 2022, 54(5): 37-42.
[21]   邱志平,陆强华. 雷达探测距离估计的非概率区间方法[J].国防科技,2008,29(2):3-6. doi:10.3969/j.issn.1671-4547.2008.02.002
QIU Z P, LU Q H. Estimation for radar detection range using non-probabilistic interval method[J]. National Defense Technology, 2008, 29(2): 3-6.
doi: 10.3969/j.issn.1671-4547.2008.02.002
[22]   OUYANG H, LIU J, HAN X, et al. Correlation propagation for uncertainty analysis of structures based on a non-probabilistic ellipsoidal model[J]. Applied Mathematical Modelling, 2020, 88: 190-207.
[23]   季熠,李彦斌,杭晓晨,等. 基于响应面代理模型的雷达天线阵面风载分析[J].工程力学,2019,36(11):222-229. doi:10.6052/j.issn.1000-4750.2018.12.0680
JI Y, LI Y B, HANG X C, et al. Wind load analysis of radar antenna based on response surface model[J]. Engineering Mechanics, 2019, 36(11): 222-229.
doi: 10.6052/j.issn.1000-4750.2018.12.0680
[24]   胡长明,操卫忠,孙为民,等. 基于代理模型的车载雷达阵面风载疲劳分析[J].强度与环境,2020,47(4):45-51.
HU C M, CAO W Z, SUN W M, et al. Fatigue analysis of vehicle radar under wind load based on surrogate models[J]. Structure & Environment Engineering, 2020, 47(4): 45-51.
[25]   SOBOL I M. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates[J]. Mathematics and Computers in Simulation, 2001, 55(1/3): 271-280.
[26]   张扬. 多参数非线性系统全局敏感性分析与动态代理模型研究[D].长沙:湖南大学,2014.
ZHANG Y. The study on global sensitivity analysis and dynamic metamodel[D]. Changsha: Hunan University, 2014.
[27]   OUYANG H, LIU J, HAN X, et al. Non-probabilistic uncertain inverse problem method considering correlations for structural parameter identification[J]. Structural and Multidisciplinary Optimization, 2021, 64(3): 1327-1342.
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