SIA OpenIR  > 智能检测与装备研究室
复杂交通环境下毫米波雷达多目标检测跟踪算法研究
Alternative TitleResearch on Multi-target Detection Algorithms for Millimeter Wave Radar in Complex Traffic Environment
高洁
Department智能检测与装备研究室
Thesis Advisor杜劲松
Keyword毫米波雷达 多目标检测 检测前跟踪 动态规划 运动模型
Pages111页
Degree Discipline控制理论与控制工程
Degree Name博士
2020-05-21
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Abstract毫米波雷达以其稳定的探测性能、全天候工作能力、良好的环境适应性,并且能同时提供目标的方位、距离、速度等多维参数信息等诸多优点,成为目前军事领域和民用应用领域的主流传感器,也成为科研机构的研究热点。目前交通应用场景中,存在固定物体如建筑物、树木、护栏等固定干扰,以及行人、非机动车等动态干扰,毫米波雷达需要在上述复杂环境下全天候、准确的区分出车辆,并监测车速、车流量、以及各种车型等状态参数,解决复杂交通环境下雷达目标检测跟踪的关键科学问题。毫米波雷达多目标检测和跟踪算法的研究为雷达智能环境感知领域的发展提供理论方法和技术支持,同时作为一种共性技术广泛应用于国防军事领域。论文以复杂交通环境下的车辆测速抓拍和流量监测为主要应用场景,针对提高微弱目标检测性能,增加多机动目标跟踪稳定性,实现非结构性和多态性的复杂交通环境下雷达感知为主要目标,以目标检测跟踪为主要突破,围绕毫米波雷达系统的目标模型、信号体制、感知算法等内容展开系统的研究工作,具体包括以下内容:(1) 运动目标及杂波模型建模方面,由于毫米波雷达探测环境复杂、目标波动明显、机动性强,传统的雷达检测跟踪方法不能够很好的满足要求,因此需要对复杂交通环境下的毫米波雷达目标运动模型、量测模型、雷达目标的波动特性,以及杂波特性进行分析建模仿真,在正确的目标模型和杂波模型基础上开展算法研究,提高毫米波雷达在复杂交通环境下的目标检测性能。(2) 在微弱目标检测方面,针对现有检测前跟踪算法中的动态规划算法在复杂的非高斯杂波环境下应用的局限性,提出了基于先验信息辅助的DP-TBD算法(PI-DP-TBD),并对有代表性的非高斯杂波场景下的目标能量指标函数进行了表达式推导,针对其中积分项无解析解的问题给出了变尺度采样算法的解决方案。(3) 多目标跟踪方面,针对DP-TBD多目标算法的计算量和复杂程度以指数形式增长的问题,结合毫米波雷达应用于交通环境场景下检测的特点,提出了基于目标分层的多目标检测前跟踪方法,分别对原有多个跟踪目标和单个新生检测目标分层进行检测前跟踪判断,把场景中的多目标检测跟踪问题转化为多个单目标检测跟踪问题,有效降低数据在动态规划算法中的计算维度。(4) 在机动目标跟踪方面,针对交互多模型算法中固定模型集的局限性,根据近程毫米波雷达扫描周期快的特点,提出一种改进的交互式多模型动态规划算法。该方法近似认为目标在动态规划算法一个循环周期内的K帧运算数据近似保持匀速直线运动,在循环周期之间结合目标的多普勒和距离信息为辅助判定条件,采用预测后的模型集滤波预测目标的状态,并根据预测的速度和方向信息,改变下一周期动态规划算法的步长范围。(5) 工程应用方面,结合上述目标检测跟踪算法,设计开发了适用于复杂交通环境下的多目标毫米波雷达,包括硬件设计、调制波形设计和处理算法设计,并针对车辆测速和流量监测两项功能进行了实验验证。
Other AbstractWith stable detection performance, all-weather working ability, good environmental adaptability, and the ability to simultaneously provide multi-dimensional parameter information such as target orientation, distance, speed and many other advantages, millimeter wave radar has become the mainstream sensing technology in the current military and civil application fields, as well as the research hotspot of scientific research institutions. At present, there are fixed objects such as buildings, trees, guardrails and other fixed interferences in traffic application scenarios, as well as dynamic interferences such as pedestrians and non motor vehicles. Millimeter wave radar not only needs to distinguish vehicles in the above-mentioned complex environment accurately, but also needs to monitor the state parameters such as vehicle speed, vehicle flow, and vehicle types. The purpose of this paper is to solve the key scientific problems of radar target detection and tracking in the complex traffic environment, and provide theoretical methods and technical support for the development of radar intelligent environment perception field. At the same time, as a common technology, it also can be widely used in the field of national defense and military. In this paper, the main application scenarios are vehicle speed capture and flow monitoring in complex traffic environment. In order to improve the detection performance of weak targets, increase the tracking stability of multiple maneuvering targets, and realize the radar perception under the complex traffic environment of non structural and polymorphism, the research work is carried out on the target model, signal system, perception algorithm and so on, with target detection and tracking algorithm as the main breakthrough. Content and innovation in this paper are as follows: (1) In the modeling of moving target and clutter model, because the MMW radar detection environment is complex, the target fluctuation is obvious, and the mobility is strong, the traditional radar detection and tracking method cannot meet the requirements well. It is necessary to model and simulate the target motion model, measurement model, target fluctuation characteristics and clutter characteristics in the complex traffic environment. Based on the correct target and clutter model, the algorithm research carries out to improve the target detection performance of MMW Radar in complex traffic environment. (2) In the aspect of weak target detection, aiming at the limitation of the dynamic programming algorithm in the existing pre detection tracking algorithm in the complex non Gaussian clutter environment, a DP-TBD algorithm (PI-DP-TBD) based on prior information assistance is proposed. The expression of the energy function in the representative non-Gaussian clutter scene is derived, and the solution of the variable scale-sampling algorithm is given for the problems of integral term and non-analytical solution. (3)In the aspect of multi-target tracking, aiming at the problem that the computation and complexity of dp-tbd multi-target algorithm increase exponentially, combined with the characteristics of MMW radar applied to traffic environment scene detection, a multi-target detection pre tracking method based on target stratification is proposed. In this algorithm, the detection and tracking problems of multiple targets in the scene transform into the detection and tracking problems of multiple single targets, which effectively reduces the calculation dimension of data in the dynamic planning algorithm. (4) In the aspect of maneuvering target tracking, aiming at the limitation of fixed model set in IMM algorithm, this paper proposes an improved interactive multi model dynamic programming algorithm according to the fast scanning period of short-range MMW radar. This method approximately considers that the K frame operation data of the target in one cycle of the dynamic planning algorithm approximately keeps the uniform linear motion, and combines the Doppler and distance information of the target as the auxiliary judgment condition between the cycles. (5) In the aspect of engineering application, this paper designs and develops a multi-target millimeter wave radar for complex traffic environment, including hardware design, modulation waveform design and processing algorithm design, and carries out experimental verification for the two functions of vehicle speed measurement and flow monitoring.
Language中文
Contribution Rank1
Document Type学位论文
Identifierhttp://ir.sia.cn/handle/173321/27170
Collection智能检测与装备研究室
Affiliation中国科学院沈阳自动化研究所
Recommended Citation
GB/T 7714
高洁. 复杂交通环境下毫米波雷达多目标检测跟踪算法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2020.
Files in This Item:
File Name/Size DocType Version Access License
复杂交通环境下毫米波雷达多目标检测跟踪算(7097KB)学位论文 开放获取CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[高洁]'s Articles
Baidu academic
Similar articles in Baidu academic
[高洁]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[高洁]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.