Aething Inc.
Pterygota Marker
Detecting drones and missiles in the video stream
Pterygota Prerequisites

System for detecting drones / missiles in the video stream

Part one. Technical description.


To understand the basics of the system for video detection of drones and missiles in a video stream, it is necessary to start with a description of existing technical solutions, their advantages and disadvantages. (Note: All information is from public sources and does not contain confidential data or detailed technical information, please contact software developers or hardware manufacturers for more details).
Also, this article does not discuss the need to introduce such a system, since this need is clear to anyone who is a little interested in world news. We will not describe here the threat itself, which has long been known to professionals and there is no need to list all the risks once again.


Any anti-drone (unmanned aerial vehicle) system consists of three components: drone detection, drone identification and tracking, and drone countermeasures.
Drone detection is the first and most necessary step, without which further technical measures are impossible. At the same time, the earliest possible detection of a drone is already partly the solution to the third stage of counteraction, since regardless of further steps and measures, the greatest response time is the key to the effectiveness of the entire system.

Existing drone detection systems include radar systems, radio signal detection systems, sound detection systems, and video stream detection systems. Let's take a closer look at the advantages and disadvantages of each system.

A historically well-known way to detect drones and missiles is a radar installation. There are many radar technologies available, full details are available on the Wikipedia website. The advantages of using radars are the greatest range and reliability of threat detection, the possibility of their use in any weather conditions (!) and time of day. Regardless of the frequencies or type of radar used (including the world's most advanced variable angle phased array radars), all radars are based on the same laws of physics, and there has been no breakthrough in this area in the last century.
Therefore, for each type of radar, the main limitation is the area (size) of the flying object, which determines the range and accuracy of object detection. Various methods are currently being used to reduce drone reflectivity for radar, but this technology is very expensive, cannot be used in mass production, and the size of the object is still the most significant factor.

Also, the size of the drone directly affects its carrying capacity and, as a result, the degree of its danger. Therefore, the direct relationship between the size of a flying object and the possibility of its long-range detection makes the radar the most reliable and stable means of detecting a threat. But, like any technology, radar has a number of disadvantages.
Not a technical, but organizational disadvantage is its cost and, as a result, the impossibility of widespread installation. The technical limitation is the terrain, which inevitably creates dead zones for the radar. A clear example is the use of low-flying drones, missiles and even aviation in a number of armed conflicts over the past decades, examples of this use are widely available on video in instant messengers and streaming platforms.

The next way to detect drones is radio detection of drone control signals or drone video transmission signals to the operator's console. The method, which is less expensive than radar, even sometimes (mainly for mass-produced drones) allows you to determine the UAV model from the imprints of its control signals. The main disadvantage of this method is its absolute uselessness when flying a drone (or rocket) that is not controlled by an operator, but uses GPS coordinates or an even more technologically advanced inertial system.

The presence of a satellite orientation system in space today is provided even in the simplest and most inexpensive drones. Inertial systems that cost tens of thousands of dollars a decade ago have also become widely available with the development of commercial drones. As for missiles using various navigation methods from thermal imagers to active methods or passive radars, the radio detection method is not applicable in principle.

Systems for detecting drones by their sound prints, in other words, by the sounds of propellers or engines, are currently only being developed. The devices we tested did not work at all (subjective remark, but based on personal testing experience), but this technology is developing and may become more reliable in the near future. Of the physically insurmountable limitations of this technology are its fundamental inoperability.

A feature within the boundaries of urban development, which is associated with an abundance of sounds. And also the unreliability of drone detection outside the city due to the presence of various noises, such as wind, sound attenuation with a distance that is practically not available at a height of a couple of hundred meters (although this height still does not allow radar to detect a drone) and noise reduction of modern drones.

So, let's take a look at the last (of the physically available at the current level of technology development) detection methods - detecting a drone in a video stream. The disadvantage of this method is the small detection range of the drone due to a number of factors. The first limitation is another law of physics of decreasing the size of an object with its removal from the camera lens. The second limitation is a non-public shortcoming of existing video analytics systems associated with the inability to distinguish objects close to the camera from objects far from the camera.
As a result, for the matrix of a digital video camera, a drone flying a few hundred meters and a fly flying a few meters from the lens have the same size. It is also worth noting that to date, there are no available systems for video detection of a drone by a video camera at all. None. A simple search query will cast doubt on this claim, as the internet and the websites of many well-known manufacturers of drone detection equipment offer such systems.

However, upon closer inspection, it turns out that all of these systems offer tracking, not drone detection. That is, they do not detect a drone and do not work as a separate system, but use coordinates from a radar or a radio detection system (both sources, except for a phased array radar costing tens of millions of dollars, give very approximate coordinates) to detect a drone and only then aim at him a video camera at known coordinates.
That is, this technology does not allow the autonomous drone detection system to work in the video stream, but requires the presence of a radar or radio detection of a drone (which in some cases does not work at all) to detect a drone.
As a result, such systems can be called drone tracking systems based on the coordinates received from other technical methods of detection, but not a system for detecting drones in a video stream, none of the systems offered by global manufacturers today works autonomously.

Now let's look at the advantages of a drone (missile, aircraft) detection system in a video stream. The main advantage of this method of determination is, oddly enough, its cost. The use of conventional video cameras (both existing and newly installed) as equipment for drone detection allows you to deploy such systems within a company, city or country.
Ensuring the life and health of people is always the highest priority for any company or state. But the impossibility of implementing such a decision due to the limited budget always makes its own objective adjustments to our capabilities.

The drone detection system in the video stream can also detect drones in the city, which, in principle, is not available for a radar that has a cost thousands of times higher than the cost of a video detection system.
The radio detection system is also often blind in urban areas, since, firstly, it has a very high radio noise level (you can imagine the number of WiFi routers in one city area), and secondly, it determines the signatures of only drone control systems known to it, leaving only self-assembly systems without attention radio control (this statement is not true for more professional radio detection systems, but their cost of tens of thousands of dollars per system does not allow it to be used in a mass installation and levels out its advantages, not to mention its uselessness when detecting drones flying along GPS coordinates) .

As we noted above, the video detection system also has limitations associated with the impossibility of distinguishing distant objects from closely flying insects. At the moment, many developers of video analytics systems claim a solution to this problem, but their technical solution is to increase the size of a moving object, which eliminates false alarms associated with flying insects, but at the same time reduces the possibility of analyzing distant objects.

Simply put, they increase the size of the area that can trigger a video analytics system alarm and, as a result, a moving object (car, person, aircraft or drone) that is large but distant from the video camera is not detected by the system.
This technological lag of video analytics systems from currently inexpensive high-resolution video cameras (up to 8K) in mass production is designed to be solved by the Pterygota Marker, which allows you to distinguish close-flying objects from distant ones and makes it possible to mass-produce video detection technology for drones (aircraft or missiles) in the video stream.

Thus the use of the Pterygota Marker can help realize the capabilities of already existing low-cost high-resolution video cameras both in drone detection systems and in other areas of video analytics systems, for example, in systems developed by car manufacturers all over the world, systems for analyzing traffic conditions or various accidents at work or eliminating rare, but financially costly false positives of various machine vision systems.
Such systems are now widely used in various industries, on the basis of such a system Tesla autopilot is built, sorting and quality control systems at industrial enterprises, and so on.

Summing up the choice of drone detection systems, it is worth noting the following. The only method available for mass adoption is the video detection method. This method provides an optimal balance between the stability and reliability of drone detection and its cost, which is always an important factor in the creation and implementation of mass spaced systems.
Such a system is practically the only method for detecting drones in the city and can be used both independently and in conjunction with other systems and types of equipment.

Long-range detection of drones is undoubtedly provided by radars, and detection of drones at high altitude is possible only with the help of radars. A drone video detection system can replace or supplement radars for detecting flying objects at low altitudes and is indispensable in urban areas.
Part two. Legal support and certification.

For further implementation of the Pterygota Marker technology in anti-drone systems (which are only one of the possible directions for the implementation of this technology), the following procedures must be carried out.

At the moment, we have filed a patent application for the use of Pterygota Marker. For the further development of this technology, an application for an invention will be filed.
The patent practice of recent years shows the real impossibility of obtaining a patent for software. This confirms the experience of patent law firms and my personal experience of trying to patent the idea of an advertising mobile application.

Obtaining a patent is necessary due to the fact that two factors are necessary for the development of this
technology: project financing to ensure software development, certification of it as a measuring instrument in metrological departments of various countries of the world, registration in institutions that provide support and development of innovative activities, such as NIST and similar companies around the world.

This will make it possible to successfully apply the data obtained using the Pterygota Marker in many industries and fields of activity, including their use in court, which is necessary when used, for example, in traffic control systems and accident investigation.

The use of the Marker for drone detection systems described above is not the main application of this technology. First of all, this technology can be used in existing video surveillance systems (from 800 million to a billion according to various sources), which will allow full use of the capabilities of already installed high-resolution cameras, and will give impetus to the development of new innovative video-based products and systems. and high-resolution thermal imaging matrices.
Part Three. Prerequisites for creation.

The creation of Pterygota Marker took personal experience and knowledge in various industries, as well as years of development and testing of various products and directions. The work of our company's employees with various equipment from atomic spectroscopes to thermal imagers and video cameras has allowed us to come to the creation of a video marker for more than ten years.
Working with software in a wide range from forensic products and software for information security to video analytics systems and various equipment and software for detecting and countering drones gave the necessary experience and knowledge.

Did you know, for example, that a thermal camera requires a standard, the so-called black body, to calibrate the readings of the instrument. It is the black body that is used by metrological services around the world for verification, that is, checking the correct operation of the thermal imager. Similarly, the Pterygota Marker will be the benchmark for video analytics systems when comparing the size of a marker with a moving object.

Known in advance dimensions of the marker and its setting from the camera lens make it possible to have a size standard with which the dimensions of other objects are compared. Experience with various computer security software allowed us to gain knowledge about the need for certification in institutions like NIST in order to be able to certify software for use in those areas where accurate data are needed about the software product used, with which data were obtained, if based on these data any decisions are made, for example, when using data from a video analytics system in court, which is especially important for car manufacturers, road traffic control systems, and so on.

Experience in manufacturing industrial equipment has given us knowledge of industrial design features and the impact of each seemingly insignificant feature on the cost of manufacturing, transporting, replacing and maintaining a product. The marker is designed taking into account the possibility of interchangeability of parts if it is necessary to change the distance of the marker relative to the camera lens, which can be caused by different focal lengths of different camera models.

The use of longitudinal reinforcement of each element of the marker will allow using it in any weather conditions, taking into account the invariance of the position of the marker under various wind loads. In order to avoid snow sticking in cold climates, the technology of the difference in thermal conductivity of the used materials of the marker itself is used, which makes it possible to remain fully visible in various weather conditions and does not require maintenance.

Many years of experience in creating various computer systems from data centers to high-load systems for calculating big data (supercomputer) and experience in creating video signal distribution systems allows us to design and create multipoint video analytics systems for our customers designed for fault-tolerant operation 24/7/365.

Finally, the experience of testing and installing various equipment for drone detection and many years of developing software for detecting drones have given us knowledge of all the advantages and disadvantages of existing drone detection systems. The automatic system for detecting and counteracting drones, which we described six years ago, has only today received a real implementation in products from many global manufacturers. At the time when we described this system, no manufacturer in the world had even a part of this solution.

The constant search for new innovative solutions allows us to be the most innovative company, creating solutions that solve a problem that our competitors do not even know about. Our experience of working directly with customers on all continents gives us inspiration and knowledge to create the most advanced and innovative solutions.
An example of the operation of a machine vision system without the PterygotA Marker and determining the depth of the volume
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