ラズパイとADS-B受信機でミニ飛行機レーダーを作ろう

wget https://www.flightaware.com/adsb/piaware/files/packages/pool/piaware/f/flightaware-apt-repository/flightaware-apt-repository_1.2_all.deb

sudo dpkg -i flightaware-apt-repository_1.2_all.deb

sudo apt update

sudo apt install -y dump1090-fa

sudo systemctl enable dump1090-fa

sudo apt install -y python3-opencv

sudo reboot

import time
import requests

# 航空機データを取得する関数
def get_aircraft_positions():
    try:
        res = requests.get("http://localhost:8080/data/aircraft.json", timeout=1)
        return [a for a in res.json().get("aircraft", []) if 'lat' in a and 'lon' in a]
    except:
        return []

# 10秒ごとに航空機データを表示
while True:
    aircraft_list = get_aircraft_positions()

    print(f"現在受信中の航空機数: {len(aircraft_list)} 機")
    for a in aircraft_list:
        hex_id = a.get('hex', '不明')
        flight = a.get('flight', hex_id).strip()
        lat = a.get('lat')
        lon = a.get('lon')
        alt = a.get('alt_baro', '不明')
        speed = a.get('gs', '不明')
        track = a.get('track', '不明')

        print(f"便名: {flight} | 緯度: {lat} | 経度: {lon} | 高度: {alt} ft | 速度: {speed} kt | 方位: {track}°")

    # 10秒待機
    time.sleep(10)

import time
import requests
import math

# 自宅の緯度・経度に変更してください（例：東京駅付近）
HOME_LAT = 35.681236
HOME_LON = 139.767125

# 航空機データを取得する関数
def get_aircraft_positions():
    try:
        res = requests.get("http://localhost:8080/data/aircraft.json", timeout=1)
        return [a for a in res.json().get("aircraft", []) if 'lat' in a and 'lon' in a]
    except:
        return []

# ハーサイン距離計算（地球上の2点間の距離をkmで返す）
def haversine(lat1, lon1, lat2, lon2):
    R = 6371.0  # 地球の半径 (km)
    lat1_rad = math.radians(lat1)
    lon1_rad = math.radians(lon1)
    lat2_rad = math.radians(lat2)
    lon2_rad = math.radians(lon2)
    dlat = lat2_rad - lat1_rad
    dlon = lon2_rad - lon1_rad
    a = math.sin(dlat/2)**2 + math.cos(lat1_rad) * math.cos(lat2_rad) * math.sin(dlon/2)**2
    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
    return R * c

# 10秒ごとに一番近い航空機を表示
while True:
    aircraft_list = get_aircraft_positions()
    closest = None
    min_distance = float('inf')

    for a in aircraft_list:
        lat = a.get('lat')
        lon = a.get('lon')
        if lat is not None and lon is not None:
            distance = haversine(HOME_LAT, HOME_LON, lat, lon)
            if distance < min_distance:
                min_distance = distance
                closest = a

    if closest:
        flight = closest.get('flight', closest.get('hex', '不明')).strip()
        print(f"最も近い便名: {flight} | 自宅からの距離: {min_distance:.2f} km")
    else:
        print("航空機データが取得できませんでした。")

    time.sleep(10)

import cv2
import requests
import numpy as np
import math
import time

# 自宅の緯度経度（例：東京駅周辺）
HOME_LAT = 35.6812
HOME_LON = 139.7671

# ウィンドウサイズと中心座標
WIDTH = 480
HEIGHT = 480
CENTER_X = WIDTH // 2
CENTER_Y = HEIGHT // 2

# 縮尺（緯度経度 → ピクセル）
SCALE = 400

# 航空機データ取得関数
def get_aircraft_positions():
    try:
        res = requests.get("http://localhost:8080/data/aircraft.json", timeout=1)
        return [a for a in res.json().get("aircraft", []) if 'lat' in a and 'lon' in a]
    except:
        return []

# 点線円を描く関数    
def draw_dotted_circle(img, center, radius, color=(0, 255, 0), spacing=2, dot_length=1):
    cx, cy = center
    circumference = 2 * math.pi * radius
    steps = int(circumference / (spacing + dot_length))

    for i in range(steps):
        angle_start = 2 * math.pi * (i * (spacing + dot_length)) / circumference
        angle_end = angle_start + (dot_length / radius)

        x1 = int(cx + radius * math.cos(angle_start))
        y1 = int(cy + radius * math.sin(angle_start))
        x2 = int(cx + radius * math.cos(angle_end))
        y2 = int(cy + radius * math.sin(angle_end))

        cv2.line(img, (x1, y1), (x2, y2), color, 1)

# 三角形で航空機を描画する関数
def draw_triangle(img, center, angle_deg, color=(0, 255, 0)):
    x, y = center
    length = 15
    width = 5
    angle_rad = math.radians(angle_deg)

    tip = (int(x + length * math.sin(angle_rad)), int(y - length * math.cos(angle_rad)))
    left = (int(x - width * math.cos(angle_rad)), int(y - width * math.sin(angle_rad)))
    right = (int(x + width * math.cos(angle_rad)), int(y + width * math.sin(angle_rad)))

    points = np.array([tip, left, right], dtype=np.int32)
    cv2.fillPoly(img, [points], color)

cv2.namedWindow("Radar Display")
cv2.resizeWindow("Radar Display", WIDTH, HEIGHT)

last_update = 0
aircraft_list = []

while True:
    frame = np.zeros((HEIGHT, WIDTH, 3), dtype=np.uint8)

    # 中心（自宅）のマーカー
    cv2.circle(frame, (CENTER_X, CENTER_Y), 2, (0, 255, 0), -1)
    
    # 緑の点線の中央縦線
    for y in range(0, HEIGHT, 10):
        if (y // 10) % 2 == 0:
            cv2.line(frame, (CENTER_X, y), (CENTER_X, y + 5), (0, 255, 0), 1)

    # 緑の点線の中央横線
    for x in range(0, WIDTH, 10):
        if (x // 10) % 2 == 0:
            cv2.line(frame, (x, CENTER_Y), (x + 5, CENTER_Y), (0, 255, 0), 1)

    # 点線円を3本描く
    for r in [60, 140, 220]:
        draw_dotted_circle(frame, (CENTER_X, CENTER_Y), r)


    # 1秒ごとにデータ更新
    if time.time() - last_update > 1.0:
        aircraft_list = get_aircraft_positions()
        last_update = time.time()

    # 各航空機を描画
    for a in aircraft_list:
        dx = (a['lon'] - HOME_LON) * SCALE
        dy = (a['lat'] - HOME_LAT) * SCALE
        x = int(CENTER_X + dx)
        y = int(CENTER_Y - dy)

        if 0 <= x < WIDTH and 0 <= y < HEIGHT:
            if 'track' in a and isinstance(a['track'], (int, float)):
                draw_triangle(frame, (x, y), a['track'])
            else:
                cv2.circle(frame, (x, y), 5, (0, 255, 0), -1)

    cv2.imshow("Radar Display", frame)

    if cv2.waitKey(30) & 0xFF == 27:  # ESCキーで終了
        break

cv2.destroyAllWindows()

git clone https://github.com/pimoroni/hyperpixel2r
cd hyperpixel2r
sudo ./install.sh

sudo nano /boot/config.txt

sudo raspi-config nonint do_i2c 1

import cv2
import requests
import numpy as np
import math
import time

# 自宅の緯度経度に変更してください（以下は東京駅周辺）
HOME_LAT = 35.6812
HOME_LON = 139.7671

# 画面サイズと中心座標
WIDTH = 480
HEIGHT = 480
CENTER_X = WIDTH // 2
CENTER_Y = HEIGHT // 2

# 緯度経度→ピクセル変換倍率
SCALE = 300

# 飛行機アイコンの読み込み（アルファチャンネル付き）
icon = cv2.imread("plane_icon.png", cv2.IMREAD_UNCHANGED)
icon_h, icon_w = icon.shape[:2]

# 背景レーダー動画の読み込み
cap = cv2.VideoCapture("radar.mp4")
fps = cap.get(cv2.CAP_PROP_FPS)
delay = int(1000 / fps) if fps > 0 else 33  # フレーム遅延時間(ms)

# 航空機データ取得関数
def get_aircraft_positions():
    try:
        res = requests.get("http://localhost:8080/data/aircraft.json", timeout=1)
        return [a for a in res.json().get("aircraft", []) if 'lat' in a and 'lon' in a]
    except:
        return []

# 飛行機アイコンを回転描画する関数
def draw_icon_rotated(img, icon, center, angle_deg):
    x, y = center
    M = cv2.getRotationMatrix2D((icon_w // 2, icon_h // 2), -angle_deg, 1.0)
    rotated = cv2.warpAffine(
        icon, M, (icon_w, icon_h),
        flags=cv2.INTER_NEAREST,
        borderMode=cv2.BORDER_CONSTANT,
        borderValue=(0, 0, 0, 0)
    )

    # アイコン貼り付け位置の計算
    x1 = x - icon_w // 2
    y1 = y - icon_h // 2
    x2 = x1 + icon_w
    y2 = y1 + icon_h

    # 画面外ならスキップ
    if x1 < 0 or y1 < 0 or x2 > img.shape[1] or y2 > img.shape[0]:
        return

    # ROI合成（アルファブレンド）
    roi = img[y1:y2, x1:x2]
    if rotated.shape[2] == 4:
        alpha = rotated[:, :, 3] / 255.0
        for c in range(3):
            roi[:, :, c] = (1 - alpha) * roi[:, :, c] + alpha * rotated[:, :, c]

# ウィンドウを全画面表示
cv2.namedWindow("Radar Display", cv2.WINDOW_NORMAL)
cv2.setWindowProperty("Radar Display", cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)

# 初期化
aircraft_list = []
last_update = 0

while True:
    now = time.time()
    if now - last_update >= 1.0:
        aircraft_list = get_aircraft_positions()
        last_update = now    
    
    # 動画フレームの読み込み
    ret, video_frame = cap.read()
    if not ret:
        cap.set(cv2.CAP_PROP_POS_FRAMES, 0)  # 動画を最初に戻す
        continue

    # 動画のリサイズ（1.8倍ズーム＋アスペクト比維持）
    video_h, video_w = video_frame.shape[:2]
    scale = min(WIDTH / video_w, HEIGHT / video_h) * 1.8
    new_w = int(video_w * scale)
    new_h = int(video_h * scale)
    resized = cv2.resize(video_frame, (new_w, new_h), interpolation=cv2.INTER_NEAREST)
    resized = cv2.convertScaleAbs(resized, alpha=0.6, beta=0)  # 薄く表示

    # 最終描画フレーム（黒背景）
    frame = np.zeros((HEIGHT, WIDTH, 3), dtype=np.uint8)

    # 動画の貼り付け位置計算（中央寄せ）
    x_offset = (WIDTH - new_w) // 2
    y_offset = (HEIGHT - new_h) // 2
    x1_dst = max(x_offset, 0)
    y1_dst = max(y_offset, 0)
    x1_src = max(-x_offset, 0)
    y1_src = max(-y_offset, 0)
    x2_dst = min(x_offset + new_w, WIDTH)
    y2_dst = min(y_offset + new_h, HEIGHT)
    x2_src = x1_src + (x2_dst - x1_dst)
    y2_src = y1_src + (y2_dst - y1_dst)

    # 動画フレームを合成
    frame[y1_dst:y2_dst, x1_dst:x2_dst] = resized[y1_src:y2_src, x1_src:x2_src]

    # 航空機データ取得
    aircraft_list = get_aircraft_positions()

    # 航空機ごとにアイコンを描画
    for a in aircraft_list:
        dx = (a['lon'] - HOME_LON) * SCALE
        dy = (a['lat'] - HOME_LAT) * SCALE
        x = int(CENTER_X + dx)
        y = int(CENTER_Y - dy)

        # 画面内に収まっているか判定
        if 0 <= x < WIDTH and 0 <= y < HEIGHT:
            if 'track' in a and isinstance(a['track'], (int, float)):
                draw_icon_rotated(frame, icon, (x, y), a['track'])
            else:
                cv2.circle(frame, (x, y), 5, (0, 255, 0), -1)

    # フレーム表示
    cv2.imshow("Radar Display", frame)

    # ESCキーで終了
    key = cv2.waitKey(delay) & 0xFF
    if key == 27:
        break

# 終了処理
cap.release()
cv2.destroyAllWindows()

sudo bash -c "$(wget -O - https://repo-feed.flightradar24.com/install_fr24_rpi.sh)"

fr24feed-status

sudo systemctl stop fr24feed
sudo systemctl disable fr24feed