Quality Assessment of Measuring the Coordinates of Airborne Objects with a Secondary Surveillance Radar

Semenets, Valerii; Svyd, Iryna; Обод, Іван; Maltsev, Oleksandr; Tkach, Mariya

doi:10.1007/978-3-030-71892-3_5

Cited by 15 publications

(3 citation statements)

References 37 publications

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“…Precision, also known as positive predictive value, tells us the probability of successfully making a correct positive classification. Equation (5) shows the formula for precision.…”

Section: Discussionmentioning

confidence: 99%

“…To make matters worse, the performance of the human eye can be reduced by cloud cover, glare from the sun, fatigue, and many other factors. With the present technologies, which include Secondary Surveillance Radar (SSR) [5], transponders, Traffic Collision Avoidance System (TCAS) [6], and, more recently, Automatic Dependent Surveillance-Broadcast (ADS-B) [7], one might think that mid-air collisions should no longer occur. However, they do happen because these technologies are not mandated equally in all countries, airspaces, or aircraft.…”

Section: Introductionmentioning

confidence: 99%

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Optical Flow-Based Obstacle Detection for Mid-Air Collision Avoidance

Vera-Yanez,

Pereira,

Rodrigues

et al. 2024

Sensors

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The sky may seem big enough for two flying vehicles to collide, but the facts show that mid-air collisions still occur occasionally and are a significant concern. Pilots learn manual tactics to avoid collisions, such as see-and-avoid, but these rules have limitations. Automated solutions have reduced collisions, but these technologies are not mandatory in all countries or airspaces, and they are expensive. These problems have prompted researchers to continue the search for low-cost solutions. One attractive solution is to use computer vision to detect obstacles in the air due to its reduced cost and weight. A well-trained deep learning solution is appealing because object detection is fast in most cases, but it relies entirely on the training data set. The algorithm chosen for this study is optical flow. The optical flow vectors can help us to separate the motion caused by camera motion from the motion caused by incoming objects without relying on training data. This paper describes the development of an optical flow-based airborne obstacle detection algorithm to avoid mid-air collisions. The approach uses the visual information from a monocular camera and detects the obstacles using morphological filters, optical flow, focus of expansion, and a data clustering algorithm. The proposal was evaluated using realistic vision data obtained with a self-developed simulator. The simulator provides different environments, trajectories, and altitudes of flying objects. The results showed that the optical flow-based algorithm detected all incoming obstacles along their trajectories in the experiments. The results showed an F-score greater than 75% and a good balance between precision and recall.

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“…Precision, also known as positive predictive value, tells us the probability of successfully making a correct positive classification. Equation (5) shows the formula for precision.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optical Flow-Based Obstacle Detection for Mid-Air Collision Avoidance

Vera-Yanez,

Pereira,

Rodrigues

et al. 2024

Sensors

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“…Це обумовлено тим, що вторинні радіолокаційні системи [4,5] забезпечують як радіолокаційне спостереження за повітряними об'єктами, обладнаними літаковими літакового відповідачами [6], так і забезпечують двосторонню передачу інформації за каналами запиту та відповіді [7,8], тобто передачу інформації між повітряними об'єктами та наземними вторинними радіолокаційними станціями. До вторинних радіолокаційних систем відносяться вторинні оглядові радіолокатори [9][10][11][12] та системи ідентифікації за ознакою «свій-чужий» [13][14][15][16][17][18]. При цьому слід зазначити, що у теперішній час існують два принципу побудови зазначених інформаційних систем [19].…”

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Comparative analysis of noise immunity of the information transmission channel of secondary radar systems

Свид¹,

Vorgul

Starokozhev³

et al. 2022

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This paper presents the conducted assessment of noise immunity of the request signal transmission channel and response channel for flight information of secondary radar systems as part of aircraft responders. The considered system is an open single-channel queuing system with refusing due to the action in the request channel of intentional and unintentional correlated and uncorrelated (intra-system) interference and ground-based receivers that receive, process and decode flight information in the presence of fluctuation and intra-system interference in the receiving channel. The results of assessing the noise immunity of the aircraft responder in the form of the aircraft responder’s readiness factor under the action of internal and deliberate interference are given. It is shown that the principle of constructing an aircraft responder and the principle of servicing request signals and transmitting flight information do not allow ensuring acceptable probabilities of obtaining flight data at ground control points.

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