WO2021051655A1 - 一种水下柔性障碍物检测系统及方法 - Google Patents

一种水下柔性障碍物检测系统及方法 Download PDF

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WO2021051655A1
WO2021051655A1 PCT/CN2019/121855 CN2019121855W WO2021051655A1 WO 2021051655 A1 WO2021051655 A1 WO 2021051655A1 CN 2019121855 W CN2019121855 W CN 2019121855W WO 2021051655 A1 WO2021051655 A1 WO 2021051655A1
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data processing
obstacles
underwater
detection system
obstacle detection
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PCT/CN2019/121855
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English (en)
French (fr)
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吕文红
王国娟
郭银景
范晓静
张建华
魏珊
葛家丽
鲍健康
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山东科技大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes

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  • the present disclosure belongs to the technical field of underwater obstacle detection, and specifically relates to an underwater flexible obstacle detection system, a corresponding detection method and application.
  • the main underwater obstacle detection mainly uses image sonar equipment.
  • image sonar is divided into fan scan sonar and side scan sonar. Multiple frames of video images of the same scene can be obtained under the condition of stationary. Therefore, the current detection technology of underwater moving obstacles is mostly based on multi-wave forward looking sonar.
  • Common underwater obstacles can be divided into two categories according to their nature: natural navigation obstacles, such as reefs, shoals, seagrass, etc.; man-made navigation obstacles, such as shipwrecks, fishing reefs, fishing fences, and marine farms.
  • natural navigation obstacles such as reefs, shoals, seagrass, etc.
  • man-made navigation obstacles such as shipwrecks, fishing reefs, fishing fences, and marine farms.
  • image processing common processing techniques include: image enhancement method, image segmentation method, image denoising method, target feature extraction and classification method, target detection method, tracking recognition method, etc.; the recognition method of forward-looking sonar continuous imaging also includes image Fusion, target detection and tracking recognition, etc.
  • flexible obstacles such as seagrass, fish, ropes, etc. have a strong absorption effect on sonar and cannot return images that can be clearly identified. Therefore, the above technical methods are not suitable for the detection of underwater flexible obstacles.
  • an underwater flexible obstacle detection system includes a supporting device, a detection device, and a data processing system;
  • the supporting equipment is used to fix the detection device and the data processing system, and to control the movement of the detection device;
  • the detection device includes a housing, a laser transmitter, a photosensitive element, and a display.
  • the laser transmitter and photosensitive element are mounted on the housing; the laser transmitter is used to emit beam laser signals, and the photosensitive element is used to receive obstacles.
  • the laser signal after the object is scattered and converted into a level signal to be sent to the data processing system; the display is used to output the obstacle signal processed by the data processing system;
  • the data processing system includes a memory, a processor, and a computer program that is stored on the processor and can run on the processor, and is characterized in that the processor executes the following data processing method: the level signal transmitted by the photosensitive element Cancellation processing is performed to eliminate the direct reflected wave component; the angle between the beam and the horizontal direction ⁇ and the vertical direction ⁇ are the independent variables, and the level signal is the dependent variable, and the mapping relationship between the angle and the level signal f( ⁇ , ⁇ ), and perform derivation and sharpening of the two-dimensional signal to obtain the relationship between the change rate of the level signal and the horizontal angle ⁇ and vertical angle ⁇ , and convert it into a visual image for display on the display.
  • the purpose of the present disclosure is to detect underwater flexible obstacles. Underwater obstacles need to be identified and classified. During the research of the present disclosure, it is found that rigid obstacles will directly reflect the laser signal emitted by the laser transmitter back to the photosensitive element. The signal reflected by the flexible obstacle includes the laser signal directly reflected on the surface of the obstacle and the laser signal returned after transmission. The degree of transmission is related to the type of obstacle. The present disclosure eliminates the part of the laser signal that is directly reflected on the surface of the obstacle through the cancellation algorithm. On the one hand, it increases the accuracy of detection. On the other hand, it can easily distinguish between rigid and flexible obstacles. Degree to realize the distinction of underwater flexible obstacles.
  • the supporting device is a pan/tilt; further, the pan/tilt is an omnidirectional pan/tilt.
  • the above-mentioned omni-directional pan/tilt is used to control the radar to perform omni-directional scanning under water.
  • the pan/tilt may use existing products in the prior art, such as the omni-directional pan/tilt described in patents 201820201127.3, 201721633529.2, 201620978306.9 or 201420316136.9.
  • the present disclosure adopts laser as the detection signal, the laser beam has good focusing performance, the laser beam has a narrow beam, high energy density, strong penetrability, and large detection distance.
  • the data processing method further includes scanning known obstacles to establish a feature set of known obstacles and images.
  • the memory is used to store the level signal converted by the photosensitive element and the feature set of known obstacles and images.
  • the detection method includes adopting the underwater flexible obstacle detection system described in the first aspect for detection.
  • the detection method specifically includes the following steps:
  • an application of the underwater flexible obstacle detection system described in the first aspect in the field of underwater obstacle detection is provided.
  • the present disclosure provides a detection system for underwater flexible obstacles, which makes up for this gap and can accurately detect underwater obstacles. The type is judged.
  • the detection technology of the present disclosure adopts laser for detection, and the laser beam has good focusing performance, the laser beam has a narrow beam, high energy density, strong penetrability, and large detection distance.
  • sonar forward-looking scanning is used in conjunction with image processing to obtain obstacle information.
  • the present disclosure also provides a corresponding obstacle information processing method for laser scanning-judging the status of flexible obstacles based on changes in level signals Types of. Through the processing of the level signal, the obstacle information can be quickly judged according to the waveform, the method is simple and the effect is remarkable.
  • the cancellation algorithm is an adaptive interference cancellation algorithm commonly used in the field.
  • the research of this disclosure introduces the cancellation algorithm.
  • the direct reflection signal of obstacles can be eliminated through cancellation to improve the detection accuracy, and on the other hand, the detection accuracy can be improved through cancellation.
  • the method realizes the recognition of underwater obstacles, and the application of mature technical solutions can solve the technical problems of the present disclosure.
  • Figure 1 is a schematic diagram of the underwater flexible obstacle detection system described in Embodiment 1;
  • 1 is a detection device
  • 2 is a photosensitive element
  • 3 is a laser transmitter
  • 4 is a pan/tilt
  • 5 is a data processing system
  • 6 is a laser signal from the laser transmitter
  • 7 is a schematic diagram of an underwater flexible obstacle.
  • Fig. 2 is a graph showing the change of the level signal intensity with time in the embodiment 1.
  • Fig. 3 is the output level change curve of the data system in the second embodiment.
  • the detection technology for underwater flexible obstacles in the prior art is still blank.
  • the present disclosure proposes an underwater flexible obstacle detection system and method.
  • an underwater obstacle detection system is provided.
  • the detection system includes a supporting device 4, a detection device 1, and a data processing system 5;
  • the supporting device 4 is used to fix the detection device 1 and the data processing system 5 and to control the movement of the detection device 1; in this embodiment, the supporting device 4 is an omnidirectional pan/tilt.
  • the detection device 1 includes a housing, a laser transmitter 3, a photosensitive element 2 and a display.
  • the laser transmitter 3 and the photosensitive element 2 are mounted on the housing; the laser transmitter 3 is used to emit beam laser signals, so The photosensitive element 2 is used to receive the laser signal scattered by the obstacle and convert it into a level signal to be sent to the data processing system; the display is used to view the obstacle signal output by the data processing system;
  • the data processing system includes a memory, a processor, and a computer program that is stored on the processor and can run on the processor, and is characterized in that the processor executes the following data processing method: the level signal transmitted by the photosensitive element Cancellation processing is performed to eliminate the direct reflected wave component; the angle between the beam and the horizontal direction ⁇ and the vertical direction ⁇ are the independent variables, and the level signal is the dependent variable, and the mapping relationship between the angle and the level signal f( ⁇ , ⁇ ), and perform derivation and sharpening of the two-dimensional signal to obtain the relationship between the rate of change of the level signal and the horizontal angle ⁇ and vertical angle ⁇ , and convert it into a visual image for display on the display.
  • the specific implementation of the cancellation algorithm in this embodiment is as follows: As shown in FIG. 2, the time when the level signal is transmitted is the origin of coordinates, the time when the level signal is received is the abscissa, and the intensity of the level signal is the ordinate. Suppose the time from the half-power point value of the level value to the maximum value is t, and the cancellation algorithm is to eliminate the 2t part of the level signal image.
  • the memory also includes a known obstacle image feature set obtained by detecting the known obstacle.
  • the detection steps of the underwater obstacle detection system described in Example 1 are as follows:
  • the photosensitive element receives the reflected laser and outputs a level signal corresponding to the laser
  • the data processing module processes the level signal, cancels the level signal sent by the photosensitive element, and eliminates the direct reflected wave component; the angle between the beam and the horizontal direction ⁇ and the vertical direction ⁇ are taken as self Variable, the level signal is the dependent variable, obtain the angle and level signal mapping relationship f( ⁇ , ⁇ ), and perform the derivation and sharpening of the two-dimensional signal to obtain the change rate of the level signal and the horizontal angle ⁇ and vertical angle ⁇ Relationship and turn it into an image;
  • the following four obstacles are taken as examples, and the detection system described in Example 1 is used to detect the four obstacles according to the detection method.
  • the result is shown in Figure 2.
  • the class I sharp pulse indicates strong reflection/ Scattering flexible obstacles, such as fish; Class II square waves, indicating non-transparent flexible obstacles; Class III sharp pulses, indicating dark flexible obstacles, such as water plants, etc.; Class IV square waves, such as transparent fishing nets.

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  • Computer Networks & Wireless Communication (AREA)
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  • General Physics & Mathematics (AREA)
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  • Optical Radar Systems And Details Thereof (AREA)

Abstract

一种水下柔性障碍物检测系统及方法，技术中针对水下障碍物的检测多集中于刚性障碍物，针对柔性障碍物的检测尚属空白。提供了一种针对水下柔性障碍物进行检测的系统及方法，系统包括云台（4）、检测装置（1）及数据处理系统（5），通过云台（4）控制激光发射器（3）对待检测区域进行均匀扫描，光敏元件（2）接收障碍物返回的信号并转换为电平信号输送至数据处理系统（5），数据处理系统（5）通过分析电平信号变化率与角度的关系获取障碍物图像，通过与已知障碍物的图像进行对比获知障碍物类型。

Description

一种水下柔性障碍物检测系统及方法 技术领域
本公开属于水下障碍物检测技术领域，具体涉及一种水下柔性障碍物检测系统、相应的检测方法及应用。
背景技术
公开该背景技术部分的信息仅仅旨在增加对本公开总体背景的理解，而不必然被视为承认或以任何形式暗示该信息构成已经成为本领域一般技术人员所公知的现有技术。
目前主要的水下障碍物检测主要采用图像声呐设备，按照扫描方式的不同图像声呐分为扇扫声呐和侧扫声呐，可以在固定不动的情况下得到同一场景的多帧视频图像。因此，目前水下运动障碍物的检测技术大多基于多波前视声呐。
水下常见障碍物按其性质可分为两大类：自然航行障碍物，如礁石、浅滩、海草等；人为航行障碍物，如沉船、渔礁、渔栅和海上养殖场等。声呐设备触碰到如礁石、沉船等硬质障碍物，会返回相应的信号，通过对声呐返回的图像进行处理获取障碍物信息。图像处理方面，常见的处理技术包括：图像增强法、图像分割法、图像去噪法、目标特征提取与分类法、目标检测法、跟踪识别法等；前视声呐连续成像的识别方法又有图像融合、目标检测和跟踪识别等。发明人认为，上述通过图像处理获取障碍物信息的方法建立在声呐前视技术的基础上，因此，上述技术通常用于水下硬质障碍物的检测。而如海草、 鱼群、绳索等柔性障碍物对声呐吸收作用较强，无法返回可供清晰识别的图像，因此，上述技术手段并不适用于水下柔性障碍物的检测。
发明内容
针对上述研究背景，发明人认为，水下无人航行中对柔性障碍物(如水草、鱼群、渔网、绳索等)的识别具有重要的应用价值，例如防止航行器被缠绕影响航行、作为海水养殖水下移动检测系统、河道湖泊水下移动检测系统等。水下柔性障碍物检测技术无论在军事还是在民用领域都有广阔的应用前景，提供一种水下柔性障碍物的检测技术具有重要意义。
为了实现上述技术效果，本公开提供以下技术方案：
本公开第一方面，提供一种水下柔性障碍物检测系统，所述检测系统包括支撑设备、检测装置及数据处理系统；
所述支撑设备用于固定检测装置及数据处理系统以及控制检测装置的移动；
所述检测装置包括壳体、激光发射器、光敏元件及显示器，所述激光发射器及光敏元件安装在壳体上；所述激光发射器用于发射波束激光信号，所述光敏元件用于接收障碍物散射后的激光信号并将其转换成电平信号输送至数据处理系统；所述显示器用于输出数据处理系统处理过的障碍物信号；
所述数据处理系统包括存储器、处理器及存储在处理器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行如下的数据处理方法：将光敏元件输送的电平信号进行对消处理，消除其中直 达反射波分量；以光束与水平方向夹角α和竖直方向夹角β为自变量，电平信号为因变量，获取角度与电平信号映射关系f(α,β)，并对二维信号进行求导锐化，获得电平信号变化率与水平角α和垂直角β的关系，并将其转化成可视图像经显示器显示。
采用对消算法消除直达波自适应干扰是本领域内提高脉冲探测技术检测精确度的常用方法。本公开目的在于对水下的柔性障碍物进行检测，需要对水下障碍物进行识别和分类，本公开研究过程中发现，刚性障碍物会将激光发射器发射的激光信号直接反射回光敏元件，柔性障碍物反射回的信号包括障碍物表面直接反射的激光信号和透射后返回的激光信号，其透射的程度与障碍物的类型呈现相关性。本公开通过对消算法消除了激光信号在障碍物表面直接反射回来的部分，一方面增加了检测的准确性，另一方面可以方便的对刚性和柔性障碍物进行区分，通过计算激光信号透射的程度，实现对水下柔性障碍物的区分。
优选的，所述支撑设备为云台；进一步的，所述云台为一种全方位云台。
上述全方位云台用于控制雷达对水下进行全方位的扫描，该云台可采用现有技术中已有的产品，例如专利201820201127.3、201721633529.2、201620978306.9或201420316136.9中记载的全方位云台。
本公开采用激光作为检测信号，激光束聚焦性能好，激光束波束窄，能量密度高，穿透性强，探测距离大。
优选的，所述数据处理方法还包括对已知障碍物进行扫描，建立已知障碍物与图像的特征集。
进一步优选的，所述存储器用于存储光敏元件转换的电平信号及已知障碍物与图像的特征集。
本公开第二方面，提供一种水下柔性障碍物的检测方法，所述检测方法包括采用第一方面所述水下柔性障碍物检测系统进行检测。
优选的，所述检测方法具体包括以下步骤：
设置云台上下左右移动，使激光发射器在水下均匀扫描障碍物，依据数据处理系统显示的图像与特征集中的图像作对比判断障碍物的类型。
本公开第三方面，提供第一方面所述水下柔性障碍物检测系统在水下障碍物检测领域的应用。
与现有技术相比，本公开的有益效果是：
1.现有技术中针对水下柔性障碍物的检测研究尚属空白，本公开提供了一种针对水下柔性障碍物的检测系统，弥补了这一空白，可以准确地对水下障碍物的类型进行判断。本公开检测技术采用激光进行检测，激光束聚焦性能好，激光束波束窄，能量密度高，穿透性强，探测距离大。
2.现有技术中采用声呐前视扫描配合图像处理获取障碍物信息，本公开针对激光扫描也提供了一种相应的障碍物信息处理方式——根据电平信号的变化来判断柔性障碍物的类型。通过对电平信号的处理，可以依据波形对障碍物信息进行快速判断，方法简便，效果显著。
3.对消算法是本领域内常用的自适应干扰消除算法，本公开研究引入对消算法，一方面可以通过对消消除障碍物的直接反射信号，提高检测准确性，另一方面通过对消方法实现对水下障碍物的识别，应用成熟的技术方案即可解决本公开的技术问题。
附图说明
构成本公开的一部分的说明书附图用来提供对本公开的进一步理解，本公开的示意性实施例及其说明用于解释本公开，并不构成对本公开的不当限定。
图1为实施例1中所述水下柔性障碍物检测系统示意图；
其中，1为检测装置，2为光敏元件，3为激光发射器，4为云台，5为数据处理系统，6为激光发射器发出的激光示意，7为水下柔性障碍物示意图。
图2为实施例1中电平信号强度随时间的变化图。
图3为实施例2中数据系统输出的电平变化曲线。
具体实施方式
应该指出，以下详细说明都是例示性的，旨在对本公开提供进一步的说明。除非另有指明，本文使用的所有技术和科学术语具有与本公开所属技术领域的普通技术人员通常理解的相同含义。
需要注意的是，这里所使用的术语仅是为了描述具体实施方式，而非意图限制根据本公开的示例性实施方式。如在这里所使用的，除非上下文另外明确指出，否则单数形式也意图包括复数形式，此外，还应当理解的是，当在本说明书中使用术语“包含”和/或“包括”时，其 指明存在特征、步骤、操作、器件、组件和/或它们的组合。
正如背景技术所介绍的，现有技术中针对水下柔性障碍物的检测技术尚属空白，为了解决如上的技术问题，本公开提出了一种水下柔性障碍物检测系统及方法。
为了使得本领域技术人员能够更加清楚地了解本公开的技术方案，以下将结合具体的实施例与对比例详细说明本公开的技术方案。
实施例1
本实施例中提供一种水下障碍检测系统，如图1所示，所述检测系统包括支撑设备4、检测装置1及数据处理系统5；
所述支撑设备4用于固定检测装置1及数据处理系统5以及控制检测装置1的移动；本实施例中，所述支撑设备4为一种全方位云台。
所述检测装置1包括壳体、激光发射器3、光敏元件2及显示器，所述激光发射器3及光敏元件2安装在壳体上；所述激光发射器3用于发射波束激光信号，所述光敏元件2用于接收障碍物散射后的激光信号并将其转换成电平信号输送至数据处理系统；所述显示器用于视出数据处理系统输出的障碍物信号；
所述数据处理系统包括存储器、处理器及存储在处理器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行如下的数据处理方法：将光敏元件输送的电平信号进行对消处理，消除其中直达反射波分量；以光束与水平方向夹角α和竖直方向夹角β为自变量，电平信号为因变量，获取角度与电平信号映射关系f(α,β)，并对二维信号进行求导锐化，获得电平信号变化率与水平角α和垂直角β的关 系，并将其转化成可视图像经显示器显示。
本实施例中对消算法的具体执行方式如下：如图2所示，以发射电平信号的时间为坐标原点，接受到电平信号的时间为横坐标，电平信号强度为纵坐标。设电平值半功率点值到最大值的时间为t，对消算法即消除电平信号图像2t部分。
另外，存储器中还包括对已知障碍进行检测得到的已知障碍物图像特征集。
实施例2
实施例1中所述水下障碍物检测系统的检测步骤如下：
(1)检测设备初始化；
(2)设置云台上下左右移动，使安装在云台上的信号发射器在水下来回均匀扫描发射激光；
(3)激光遇到障碍物发生反射，光敏元件接收到反射后的激光，并输出与激光相对应的电平信号；
(4)数据处理模块对电平信号进行处理，将光敏元件输送的电平信号进行对消处理，消除其中直达反射波分量；以光束与水平方向夹角α和竖直方向夹角β为自变量，电平信号为因变量，获取角度与电平信号映射关系f(α,β)，并对二维信号进行求导锐化，获得电平信号变化率与水平角α和垂直角β的关系并将其转成图像；
(5)通过对比图像与已知障碍物的图像来判断水下柔性障碍物的类型及大小。
本实施例中以下列四种障碍物为例，采用实施例1中所述检测系 统依照该检测方法对四种障碍物进行检测，结果如图2所示，I类尖脉冲，表示强反射/散射柔性障碍物，如鱼等；II类方波，表示非透明柔性障碍物；III类尖脉冲，表示深色柔性障碍物，如水草等；IV类方波，如透明渔网等。
以上所述仅为本公开的优选实施例而已，并不用于限制本公开，对于本领域的技术人员来说，本公开可以有各种更改和变化。凡在本公开的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本公开的保护范围之内。

Claims (10)

  1. 一种水下柔性障碍物检测系统，其特征在于，所述检测系统包括支撑设备、检测装置和数据处理系统；
    所述支撑设备用于固定检测装置及数据处理系统以及控制检测装置的移动；
    所述检测装置包括壳体、激光发射器、光敏元件及显示器，所述激光发射器及光敏元件安装在壳体上；所述激光发射器用于发射波束激光信号，所述光敏元件用于接收障碍物散射后的激光信号并将其转换成电平信号输送至数据处理系统；所述显示器用于视出数据处理系统输出的障碍物信号。
  2. 如权利要求1所述水下柔性障碍物检测系统，其特征在于，所述数据处理系统包括存储器、处理器及存储在处理器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行如下的数据处理方法：将光敏元件输送的电平信号进行对消处理，消除其中直达反射波分量；以光束与水平方向夹角α和竖直方向夹角β为自变量，电平信号为因变量，获取角度与电平信号映射关系f(α,β)，并对二维信号进行求导锐化，获得电平信号变化率与水平角α和垂直角β的关系，并将其转化成可视图像经显示器显示。
  3. 如权利要求1所述水下柔性障碍物检测系统，其特征在于，所述支撑设备为云台。
  4. 如权利要求3所述水下柔性障碍物检测系统，其特征在于，所述云台为一种全方位云台。
  5. 如权利要求1所述水下柔性障碍物检测系统，其特征在于，采用 激光发射器发射激光信号。
  6. 如权利要求1所述水下柔性障碍物检测系统，其特征在于，所述数据处理方法还包括对已知障碍物进行扫描，建立已知障碍物与图像的特征集。
  7. 如权利要求6所述水下柔性障碍物检测系统，其特征在于，所述存储器用于存储光敏元件转换的电平信号及已知障碍物与图像的特征集。
  8. 一种水下柔性障碍物的检测方法，其特征在于，所述检测方法包括采用权利要求1-7任一项所述水下柔性障碍物检测系统进行检测。
  9. 如权利要求8所述水下柔性障碍物的检测方法，其特征在于，所述检测方法具体包括以下步骤：设置云台上下左右移动，使激光发射器发射激光信号对障碍物进行均匀扫描，依据数据处理系统显示的图像与特征集中的图像作对比判断障碍物的类型。
  10. 权利要求1-7任一项所述水下柔性障碍物检测系统在水下障碍物检测领域的应用。
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