CN108173978A - UAV detection method based on smart device parsing Wi-Fi MAC address - Google Patents

The invention discloses a kind of unmanned plane detection methods based on smart machine parsing Wi Fi MAC Address, mainly solve the problems, such as that existing unmanned plane detection method is complicated, of high cost and detection performance is insufficient, implementation step is：Wi Fi beacon frames in space are captured by smart machine, parse the MAC Address of information source in the Wi Fi beacon frames captured；The MAC Address list obtained using parsing, realize the detection of unmanned plane, in the case of the MAC Address field of known unmanned plane producer, using the method for MAC Address prefix matching, in the case of the MAC Address field of unknown unmanned plane producer, using multiple smart machine collaborative perceptions, the method for detection；The present invention takes full advantage of unmanned plane in flight course, it needs to carry out the characteristic of image video signal transmission and the function of smart machine support Wi Fi connections in real time, unmanned machine testing is completed by parsing, matching MAC Address, testing cost and complexity are significantly reduced, there is important application value in unmanned plane detection field.

基于智能设备解析Wi-Fi MAC地址的无人机检测方法UAV detection method based on smart device parsing Wi-Fi MAC address

技术领域technical field

本发明属于目标检测技术领域，尤其涉及低空慢速小目标检测，具体是一种基于智能设备解析Wi-Fi MAC地址的无人机检测方法。The invention belongs to the technical field of target detection, and in particular relates to low-altitude slow-speed small target detection, in particular to a UAV detection method based on intelligent equipment parsing Wi-Fi MAC addresses.

背景技术Background technique

近年来，以多旋翼无人机为主的小型民用无人机市场迎来了井喷式地增长，无人机已广泛应用到工业、军事、民用等多个领域。然而，无人机市场的快速增长也带来了安全与隐私方面的问题，无人机的“黑飞”、“滥飞”事件在国内外频繁发生，严重危害个人隐私安全、公共场所安全、航空安全以及国家安全。可见，为应对频发的无人机的“黑飞”、“滥飞”事件对个体及公共安全造成的挑战，对入侵特定区域的无人机进行及时、有效的检测已迫在眉急。In recent years, the small civilian UAV market dominated by multi-rotor UAVs has ushered in a blowout growth. UAVs have been widely used in many fields such as industry, military, and civilian use. However, the rapid growth of the UAV market has also brought about security and privacy issues. Incidents of "black flying" and "indiscriminate flying" of UAVs have occurred frequently at home and abroad, seriously endangering personal privacy, public places, and public places. aviation safety and national security. It can be seen that in order to cope with the challenges to individual and public safety caused by frequent "black flying" and "indiscriminate flying" incidents of drones, timely and effective detection of drones invading specific areas is urgent.

一般对于飞行物体的检测，有三类方法，分别是基于雷达，基于红外或摄像机等视觉设备以及基于麦克风阵列等音频设备的检测方法。然而这些方法不能很好地适应目前对于无人机检测的需求。首先，因为无人机体型较小，其有效的信号反射面积很小，使得雷达的回波信号能量很小，容易淹没在噪声中。其次，无人机经常出没于城市环境中，雷达系统本身很强的电磁辐射，难以在城市内布置。另外，无人机可以低空飞行，使得红外或摄像机等视觉设备的视线容易被树木，建筑等所遮挡。再者，由于空间中的声音噪声，无人机的音频信号的信噪比较低，使得麦克风阵列等音频设备难以检测。另一方面，无人机在飞行过程中，为了使飞手了解到无人机的位置，高度等信息以及更好地进行航拍，会实时地向飞手发送视频信号。大多数无人机都采用Wi-Fi技术来传输器视频信号。而智能设备具有感知Wi-Fi信号的能力，并可以对空间中的Wi-Fi信号进行解析。综上所述，利用智能设备对Wi-Fi信号的感知能力来检测无人机具有很好的可行性。Generally, there are three types of methods for the detection of flying objects, which are based on radar, based on visual devices such as infrared or cameras, and based on audio devices such as microphone arrays. However, these methods are not well suited to the current needs of UAV detection. First of all, because the UAV is small in size, its effective signal reflection area is very small, so that the echo signal energy of the radar is very small, and it is easy to be submerged in the noise. Secondly, drones often appear in urban environments, and the radar system itself has strong electromagnetic radiation, making it difficult to deploy in cities. In addition, UAVs can fly at low altitudes, making the sight of visual devices such as infrared or cameras easily blocked by trees, buildings, etc. Furthermore, due to the acoustic noise in the space, the signal-to-noise ratio of the drone's audio signal is low, making it difficult to detect audio devices such as microphone arrays. On the other hand, during the flight of the drone, in order to let the pilot know the position, height and other information of the drone and take better aerial photography, it will send video signals to the pilot in real time. Most drones use Wi-Fi technology to transmit video signals. Smart devices have the ability to perceive Wi-Fi signals and can analyze Wi-Fi signals in space. To sum up, it is very feasible to use the perception ability of smart devices to Wi-Fi signals to detect UAVs.

发明内容Contents of the invention

本发明的目的在于针对现有无人机检测技术系统复杂、成本高以及检测性能不足的问题，提出一种基于智能设备解析Wi-Fi MAC地址的无人机检测方法。该方法一方面充分利用无人机在飞行过程中，需要实时地进行图像视频信号传输的特性；另一方面充分利用了智能设备支持Wi-Fi连接的功能。本发明提出的基于智能设备解析Wi-Fi MAC地址的无人机检测方法，不需要专用的检测设备，成本低廉，检测方便，便于广泛推广，可以有效地进行无人机检测。The purpose of the present invention is to propose a UAV detection method based on smart device parsing Wi-Fi MAC address for the problems of complex system, high cost and insufficient detection performance of the existing UAV detection technology. On the one hand, this method makes full use of the characteristics that the UAV needs to transmit image and video signals in real time during the flight; on the other hand, it makes full use of the function of smart devices supporting Wi-Fi connection. The UAV detection method proposed by the present invention based on intelligent equipment parsing Wi-Fi MAC addresses does not require special detection equipment, is low in cost, convenient in detection, easy to be widely promoted, and can effectively detect UAVs.

本发明的目的是通过以下技术方案来实现的：一种基于智能设备解析Wi-Fi MAC地址的无人机检测方法，包含以下步骤：The object of the present invention is achieved through the following technical solutions: a method for detecting drones based on smart devices resolving Wi-Fi MAC addresses, comprising the following steps:

(1)通过智能设备捕获空间中的Wi-Fi信标帧，解析捕获到的Wi-Fi信标帧中信源的MAC地址；(1) Capture the Wi-Fi beacon frame in the space through the smart device, and analyze the MAC address of the source in the captured Wi-Fi beacon frame;

(2)利用步骤(1)解析得到的MAC地址列表，实现无人机的检测，包括：(2) Utilize the MAC address list that step (1) resolves to obtain, realize the detection of unmanned aerial vehicle, including:

在已知无人机厂家的MAC地址字段的情况下，采用MAC地址前缀匹配的方法，具体地，MAC地址一共有48位，而其前24位为组织唯一标志符，由IEEE的注册管理机构统一分配；组织唯一标志符唯一标识了厂家；因而，如果解析得到的MAC地址列表中，存在前24位与无人机厂家的组织唯一标志符相同的MAC地址，则前缀匹配成功，说明检测到了无人机；When the MAC address field of the drone manufacturer is known, the MAC address prefix matching method is adopted. Specifically, the MAC address has a total of 48 bits, and the first 24 bits are the unique identifier of the organization. Uniform distribution; the unique identifier of the organization uniquely identifies the manufacturer; therefore, if there is a MAC address with the same first 24 digits as the unique identifier of the drone manufacturer in the MAC address list obtained by parsing, the prefix match is successful, indicating that a drone has been detected. UAV;

如果无法提前知道无人机的MAC地址，则可以采用多个智能设备协同感知、检测的方法；具体地，利用无人机与路由器等其他无线接入点在可移动性上的不同，通过收集同一时间段内，多个彼此距离较远的用户的数据，然后检查这些用户的数据中是否有某些相同的MAC地址，如果有，则说明该MAC地址为无人机的MAC地址，从而实现检测；If the MAC address of the UAV cannot be known in advance, the method of cooperative perception and detection of multiple smart devices can be adopted; specifically, the difference in mobility between UAVs and other wireless access points such as routers can be used to collect In the same time period, the data of multiple users who are far away from each other, and then check whether there are some identical MAC addresses in the data of these users. If there is, it means that the MAC address is the MAC address of the drone, so as to realize detection;

如果没有检测到无人机，则跳到步骤(1)，继续记录Wi-Fi信标帧。If no drone is detected, skip to step (1) and continue recording Wi-Fi beacon frames.

进一步地，所述智能设备还应具有解析隐藏SSID的信标帧的功能。Further, the smart device should also have the function of parsing the beacon frame with the hidden SSID.

本发明与现有技术相比具有以下优点：Compared with the prior art, the present invention has the following advantages:

(1)本发明采用智能设备来实现无人机检测，无需专用检测设备，成本低廉；(1) The present invention adopts intelligent equipment to realize unmanned aerial vehicle detection, does not need special detection equipment, and the cost is low;

(2)本发明充分利用了充分利用无人机在飞行过程中，需要实时地进行图像视频信号传输的特性以及智能设备支持Wi-Fi连接的功能，通过解析、匹配MAC地址来完成无人机检测，检测方便，降低了系统复杂度。(2) The present invention makes full use of the characteristics of real-time image and video signal transmission and the function of smart devices to support Wi-Fi connection during the flight of the drone, and completes the unmanned aerial vehicle by parsing and matching the MAC address. Detection, detection is convenient, reducing system complexity.

附图说明Description of drawings

图1是本发明的方法流程框图。Fig. 1 is a flow chart of the method of the present invention.

图2是本发明的MAC匹配过程示意图。Fig. 2 is a schematic diagram of the MAC matching process of the present invention.

具体实施方式Detailed ways

以下参照附图，对本发明的技术方案和效果作进一步的详细说明。The technical solutions and effects of the present invention will be further described in detail below with reference to the accompanying drawings.

对于无人机的检测，传统的方法主要有雷达、视频、音频三种方法。而这些方法在无人机检测的场景下，都有一些局限性。本发明考虑到无人机在飞行过程中，为了便于飞手更好地进行航拍，或者更好地控制无人机的飞行状态，无人机都会实时地向飞手发送视频信息。而目前市面上，大多数无人机所使用的无线视频传输是基于Wi-Fi技术的。对于无人机所采用的Wi-Fi技术，具体而言，无人机中有一个Wi-Fi模块，其作用相当于一个接入点；为了告知其他节点它的存在，无人机上的Wi-Fi模块会不断地广播其信标帧。信标帧中包含了其自身的MAC地址。本发明正是利用智能设备获取Wi-Fi信标帧，并通过识别信标帧中的MAC地址来检测无人机，参照图1，本发明的实现步骤如下：For the detection of drones, the traditional methods mainly include radar, video, and audio. However, these methods have some limitations in the UAV detection scenario. The present invention considers that during the flight of the UAV, in order to facilitate the pilot to take better aerial photography, or to better control the flight state of the UAV, the UAV will send video information to the pilot in real time. Currently on the market, the wireless video transmission used by most drones is based on Wi-Fi technology. For the Wi-Fi technology adopted by drones, specifically, there is a Wi-Fi module in the drone, which acts as an access point; in order to inform other nodes of its existence, the Wi-Fi module on the drone The Fi module continuously broadcasts its beacon frames. The beacon frame contains its own MAC address. The present invention utilizes the smart device to obtain the Wi-Fi beacon frame, and detects the unmanned aerial vehicle by identifying the MAC address in the beacon frame. With reference to Fig. 1, the implementation steps of the present invention are as follows:

步骤一：在智能设备上安装Wi-Fi分析软件，该软件应具有获取Wi-Fi列表，并能解析出Wi-Fi信标帧中MAC地址的功能。特别地，为了应对接入点隐藏自身SSID的情况，Wi-Fi分析软件还应该具有获取隐藏SSID的接入点的信标帧，并能解析其MAC地址的功能。Step 1: Install Wi-Fi analysis software on the smart device. The software should have the function of obtaining the Wi-Fi list and parsing out the MAC address in the Wi-Fi beacon frame. In particular, in order to deal with the situation where the access point hides its own SSID, the Wi-Fi analysis software should also have the function of obtaining the beacon frame of the access point with the hidden SSID and analyzing its MAC address.

步骤二：开启智能设备上的WLAN功能，并打开智能设备上的Wi-Fi分析软件，记录空间中的Wi-Fi信标帧。Step 2: Turn on the WLAN function on the smart device, and open the Wi-Fi analysis software on the smart device to record the Wi-Fi beacon frames in the space.

步骤三：解析捕获到的信标帧中的MAC地址。根据802.11的标准，信标帧中包含3个MAC地址字段，其中第一个为FF:FF:FF:FF:FF:FF，即广播地址，后面两个地址字段相同，为信源的MAC地址。在无人机检测的场景中，即是无人机上的Wi-Fi模块的MAC地址。因此，需要利用Wi-Fi分析软件，解析出信源的MAC地址。Step 3: Analyzing the MAC address in the captured beacon frame. According to the 802.11 standard, the beacon frame contains 3 MAC address fields, the first of which is FF:FF:FF:FF:FF:FF, which is the broadcast address, and the latter two address fields are the same, which is the MAC address of the source . In the scenario of drone detection, it is the MAC address of the Wi-Fi module on the drone. Therefore, it is necessary to use Wi-Fi analysis software to analyze the MAC address of the source.

步骤四：通过步骤二中解析得到的MAC地址，进行无人机检测。进行检测的过程，根据是否已知无人机厂家MAC地址可以分为两种情况。第一种情况是提前知道了无人机厂家的MAC地址字段。在这种情况下，可以利用步骤二中解析到的MAC地址列表，与无人机厂家的MAC字段进行对比；因为，一般地，无人机厂家有着固定字段的MAC地址，其MAC地址中，前24位是固定的，例如深圳市大疆创新科技有限公司的产品，其固定字段为60:60:1F。因此如果发现解析到的MAC地址的前24位与无人机厂家MAC地址的固定字段相同，则可以说明检测到无人机。第二种情况是无法提前知道无人机厂家的MAC地址字段。在这种情况下，可以利用无人机与路由器在可移动性上的不同，并通过多个智能设备协同工作来对无人机进行检测。具体而言，考虑到无人机在飞行过程中是不断运动的，因而相比于路由器等固定的、静态的无线接入点，无人机有着很强的移动性。这就使得在无人机较长的飞行路径上的用户都可以接受到无人机的信标帧，进而获取其MAC地址。而一个固定的、静态的路由器，其覆盖范围有限，通常在50米左右。当用户与路由器距离渐远时，由于无线信号的衰减，该用户无法接收到该路由器的信标帧。虽然此时从单个用户的数据中，不知道哪一个MAC地址就是无人机的，但是，通过收集同一时间段内，多个彼此距离较远的用户的数据，然后检查这些用户的数据中，有没有某些相同的MAC地址。如果有，则说明该MAC地址为无人机的MAC地址，从而实现检测。Step 4: Use the MAC address analyzed in step 2 to detect the drone. The detection process can be divided into two cases according to whether the MAC address of the drone manufacturer is known. The first situation is to know the MAC address field of the drone manufacturer in advance. In this case, you can use the MAC address list parsed in step 2 to compare with the MAC field of the drone manufacturer; because, generally, the drone manufacturer has a MAC address with a fixed field, and in its MAC address, The first 24 bits are fixed, for example, the products of Shenzhen Dajiang Innovation Technology Co., Ltd. have a fixed field of 60:60:1F. Therefore, if the first 24 bits of the parsed MAC address are found to be the same as the fixed field of the drone manufacturer's MAC address, it means that the drone has been detected. The second situation is that the MAC address field of the drone manufacturer cannot be known in advance. In this case, the difference in mobility between the UAV and the router can be utilized, and multiple smart devices can work together to detect the UAV. Specifically, considering that drones are constantly moving during flight, compared with fixed and static wireless access points such as routers, drones have strong mobility. This allows users on the long flight path of the drone to receive the beacon frame of the drone, and then obtain its MAC address. And a fixed, static router, its coverage is limited, usually about 50 meters. When the distance between the user and the router is getting farther, due to the attenuation of the wireless signal, the user cannot receive the beacon frame of the router. Although at this time from the data of a single user, it is not known which MAC address belongs to the drone, but by collecting the data of multiple users who are far away from each other within the same time period, and then checking the data of these users, Is there some same MAC address. If there is, it means that the MAC address is the MAC address of the drone, so as to realize the detection.

如果没有检测到无人机，则跳到步骤一，继续记录Wi-Fi信标帧。当人为决定结束检测时，关闭系统，跳出循环。If no drone is detected, skip to step 1 and continue recording Wi-Fi beacon frames. When the human decides to end the detection, shut down the system and jump out of the loop.

综上所述，本发明主要解决了现有无人机检测技术系统复杂、成本高以及检测性能不足的问题，一方面充分利用无人机在飞行过程中，需要实时地进行图像视频信号传输的特性；另一方面充分利用了智能设备支持Wi-Fi连接的功能。本发明提出的基于智能设备解析Wi-Fi MAC地址的无人机检测方法，不需要专用的检测设备，成本低廉，检测方便，便于广泛推广，可以有效地进行无人机检测。To sum up, the present invention mainly solves the problems of complex system, high cost and insufficient detection performance of the existing UAV detection technology. characteristics; on the other hand, it takes full advantage of the smart device's ability to support Wi-Fi connections. The UAV detection method proposed by the present invention based on intelligent equipment parsing Wi-Fi MAC addresses does not require special detection equipment, is low in cost, convenient in detection, easy to be widely promoted, and can effectively detect UAVs.