# An ADS-B Information-Based Collision Avoidance Methodology to UAV

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## Abstract

**:**

## 1. Introduction

## 2. Flight Conflict Perception and Prediction

#### 2.1. ADS-B Technology

#### 2.2. ADS-B Message Structure

#### 2.3. Trajectory Prediction Based on UKF

#### 2.3.1. Unscented Transformation (UT)

#### 2.3.2. Main Steps of the UKF Algorithm

- Step 1: Build a system state model.

- Step 2: Input parameters.

- Step 3: Use Gaussian distribution to generate sigma sampling points.

- Step 4: Calculation of sigma test point weight.

- Step 5: Predict the new state equation.

- Step 6: Measurement status update.

- Step 7: Covariance matrix of state measurements.

- Step 8: State update and covariance matrix update.

## 3. Flight Conflict Relief

#### 3.1. Flight Conflict Resolution Model

**Definition**

**1.**

#### 3.2. Flight Conflict Resolution Strategies

#### 3.2.1. Speed Deliverance

#### 3.2.2. Heading Deliverance

#### 3.2.3. Compound Deliverance

## 4. UAV Conflict Resolution Strategy Selection Process

## 5. Simulation Verification

#### 5.1. Track Prediction Verification

#### 5.2. Conflict Resolution under Different Resolution Strategies

#### 5.2.1. Speed Deliverance

#### 5.2.2. Sailing to Deliverance

#### 5.2.3. Compound Deliverance

## 6. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## Abbreviations

UAV | Unmanned Aerial Vehicle |

ADS-B | Automatic Dependent Surveillance-Broadcast |

TCAS | Traffic Collision Avoidance System |

UKF | Unscented Kalman Filter |

ICAO | International Civil Aviation Organization |

AES | Aircraft Earth Station |

ACARS | Aircraft Communications Addressing and Reporting System |

RGS | Remote Ground Station |

KF | Kalman Filtering |

EKF | Extended Kalman Filter |

UT | Unscented Transformation |

VO | Velocity Obstacle |

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**Figure 8.**Analysis of UKF and EKF track prediction results: (

**a**) UKF and EKF trajectory forecast; (

**b**) UKF and EKF latitude and longitude coordinates prediction error size; (

**c**) combined UKF and EKF prediction errors.

**Figure 10.**Voyage deliverance scenario analysis: (

**a**) navigate to the relief scene; (

**b**) two-machine interval.

**Figure 11.**The relationship between the amount of speed change and the amount of heading change, and the integrated utility function: (

**a**) the amount of speed change and heading change; (

**b**) amount of velocity change and integrated utility function.

**Figure 12.**Compound relief scenario analysis: (

**a**) compound deliverance scenario; (

**b**) two-machine interval.

Error Size (m) | UKF | EKF |
---|---|---|

Latitude error | 166.4777 | 362.3431 |

Longitude error | 101.9416 | 141.5749 |

Integrated error | 3.5274 | 6.9972 |

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**MDPI and ACS Style**

Tong, L.; Gan, X.; Wu, Y.; Yang, N.; Lv, M.
An ADS-B Information-Based Collision Avoidance Methodology to UAV. *Actuators* **2023**, *12*, 165.
https://doi.org/10.3390/act12040165

**AMA Style**

Tong L, Gan X, Wu Y, Yang N, Lv M.
An ADS-B Information-Based Collision Avoidance Methodology to UAV. *Actuators*. 2023; 12(4):165.
https://doi.org/10.3390/act12040165

**Chicago/Turabian Style**

Tong, Liang, Xusheng Gan, Yarong Wu, Nan Yang, and Maolong Lv.
2023. "An ADS-B Information-Based Collision Avoidance Methodology to UAV" *Actuators* 12, no. 4: 165.
https://doi.org/10.3390/act12040165