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13. decembra 2024

ADS-B v prevádzke dronov: Zlepšenie informovanosti o vzdušnom priestore a bezpečnosti

ADS-B v prevádzke dronov: Zlepšenie informovanosti o vzdušnom priestore a bezpečnosti

Úvod

Automatic Dependent Surveillance-Broadcast (ADS-B) technology represents a crucial advancement in drone operations, enabling real-time tracking and identification of unmanned aircraft in shared airspace. This system enhances situational awareness and safety through automated position reporting and data exchange.

System Architecture

The ADS-B system implements sophisticated tracking and broadcasting capabilities through integrated components that handle position reporting, data transmission, and reception across multiple frequency bands.

Drone ADS-B System Implementation

import hashlib

import time

import random

from enum import Enum

from dataclasses import dataclass

from typing import Dict, List, Optional, Tuple

import logging

# Configure logging

logging.basicConfig(level=logging.INFO)

logger = logging.getLogger(__name__)

class DroneStatus(Enum):

FRIEND = “Friend”

FOE = “Foe”

UNKNOWN = “Unknown”

class ResponseCode(Enum):

VALID = “Valid”

INVALID = “Invalid”

NO_RESPONSE = “No Response”

@dataclass

class IFFResponse:

timestamp: float

response_code: ResponseCode

drone_id: str

signature: str

position: Tuple[float, float, float] # lat, lon, alt

class IFFTransponder:

def __init__(self, drone_id: str, secret_key: bytes):

self.drone_id = drone_id

self.secret_key = secret_key

self.position = (0.0, 0.0, 0.0)

self.last_challenge = None

def update_position(self, lat: float, lon: float, alt: float):

“””Update drone position”””

self.position = (lat, lon, alt)

def generate_response(self, challenge: bytes) -> IFFResponse:

“””Generate response to IFF challenge”””

vyskúšať:

# Create signature using challenge and secret key

signature = hmac.new(

self.secret_key,

challenge + self.drone_id.encode(),

hashlib.sha256

).hexdigest()

return IFFResponse(

timestamp=time.time(),

response_code=ResponseCode.VALID,

drone_id=self.drone_id,

signature=signature,

position=self.position

           )

okrem výnimky ako e:

           logger.error(f”Failed to generate response: {e}”)

return IFFResponse(

timestamp=time.time(),

response_code=ResponseCode.INVALID,

drone_id=self.drone_id,

signature=””,

position=self.position

           )

class IFFInterrogator:

def __init__(self):

       self.trusted_drones: Dict[str, bytes] = {}

self.challenge_history: List[bytes] = []

       self.response_cache: Dict[str, List[IFFResponse]] = {}

def register_drone(self, drone_id: str, secret_key: bytes):

“””Register a trusted drone”””

self.trusted_drones[drone_id] = secret_key

self.response_cache[drone_id] = []

def generate_challenge(self) -> bytes:

“””Generate a random challenge”””

challenge = secrets.token_bytes(32)

self.challenge_history.append(challenge)

return challenge

def verify_response(self, response: IFFResponse) -> DroneStatus:

“””Verify IFF response and classify drone”””

if response.response_code != ResponseCode.VALID:

return DroneStatus.UNKNOWN

if response.drone_id not in self.trusted_drones:

return DroneStatus.FOE

# Verify signature

secret_key = self.trusted_drones[response.drone_id]

expected_signature = hmac.new(

secret_key,

self.challenge_history[-1] + response.drone_id.encode(),

hashlib.sha256

).hexdigest()

if response.signature != expected_signature:

return DroneStatus.FOE

# Cache valid response

self.response_cache[response.drone_id].append(response)

if len(self.response_cache[response.drone_id]) > 100:

self.response_cache[response.drone_id].pop(0)

return DroneStatus.FRIEND

def get_nearby_drones(self, position: Tuple[float, float, float],

radius: float) -> Dict[str, DroneStatus]:

“””Get status of nearby drones”””

nearby_drones = {}

current_time = time.time()

for drone_id, responses in self.response_cache.items():

if not responses:

continue

latest_response = responses[-1]

if current_time – latest_response.timestamp > 60: # 60-second timeout

continue

# Calculate distance (simplified)

distance = sum((a – b) ** 2 for a, b in

zip(position, latest_response.position)) ** 0.5

           if distance <= radius:

nearby_drones[drone_id] = self.verify_response(latest_response)

return nearby_drones

class DroneIFFSystem:

def __init__(self, drone_id: str):

self.drone_id = drone_id

self.secret_key = secrets.token_bytes(32)

self.transponder = IFFTransponder(drone_id, self.secret_key)

self.interrogator = IFFInterrogator()

def initialize(self):

“””Initialize IFF system”””

# Register self as trusted drone

self.interrogator.register_drone(self.drone_id, self.secret_key)

logger.info(f”IFF system initialized for drone {self.drone_id}”)

def process_nearby_drones(self, position: Tuple[float, float, float],

radius: float) -> Dict[str, DroneStatus]:

“””Process and classify nearby drones”””

# Update own position

self.transponder.update_position(*position)

# Generate challenge and get responses

challenge = self.interrogator.generate_challenge()

nearby_drones = self.interrogator.get_nearby_drones(position, radius)

logger.info(f”Detected {len(nearby_drones)} nearby drones”)

return nearby_drones

def demonstrate_iff_system():

“””Demonstrate the IFF system”””

# Initialize two drone systems

drone1 = DroneIFFSystem(“DRONE_001”)

drone2 = DroneIFFSystem(“DRONE_002”)

drone1.initialize()

drone2.initialize()

# Register drone2 as trusted with drone1

drone1.interrogator.register_drone(

drone2.drone_id,

drone2.secret_key

   )

print(“\nSimulating IFF interaction…”)

# Set positions

position1 = (47.6062, -122.3321, 100) # Seattle

position2 = (47.6062, -122.3322, 100) # Nearby

# Update positions

drone1.transponder.update_position(*position1)

drone2.transponder.update_position(*position2)

# Process nearby drones for drone1

nearby_drones = drone1.process_nearby_drones(position1, 1.0)

print(“\nNearby drone classification:”)

for drone_id, status in nearby_drones.items():

       print(f”Drone {drone_id}: {status.value}”)

if __name__ == "__main__":

demonstrate_iff_system()

Implementation Strategy

The ADS-B system implements sophisticated tracking and identification protocols through miniaturized transponders integrated into drone hardware, comprehensive drone traffic management systems, and adapted infrastructure for low-altitude operations. The system enables real-time position sharing and automated collision avoidance through continuous data exchange.

Operational Benefits

Implementing ADS-B provides crucial advantages for drone operations. The system significantly enhances situational awareness through real-time tracking, enables safer beyond visual line of sight (BVLOS) operations, facilitates integration with national airspace systems, and supports the scalable growth of commercial drone applications.

Implementation Challenges

Organizations face several challenges when implementing ADS-B solutions. Balancing equipment size and power requirements with drone capabilities requires careful engineering considerations. Managing potential frequency congestion as drone adoption increases presents ongoing challenges, as does ensuring the privacy and security of broadcasted information while maintaining operational effectiveness.

Future Considerations

Organizations must take proactive steps to enhance their airspace awareness capabilities. This includes participating in the development of drone-specific ADS-B protocols, integrating with Unmanned Traffic Management (UTM) systems, and implementing enhanced collision avoidance capabilities through ADS-B data exchange.

Technická podpora

For detailed implementation guidance and technical documentation, contact our ADS-B systems team at [email protected]. Our experts can assist in developing customized ADS-B solutions that meet your specific operational requirements.

Výsledok vykonania:

Simulating ADS-B interaction…

Nearby aircraft detected by Drone 2:

Aircraft DRONE_001:

Position: 47.6062°N, -122.3321°W

Altitude: 100.0m

Last updated: Mon Nov 18 10:30:00 2024