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import pandas as pd
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import numpy as np
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def generate_adsb_test_data(normal_count=120, attack_count=80):
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"""
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生成ADS-B测试数据
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normal_count: 正常数据条数
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attack_count: 攻击数据条数
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"""
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data = []
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# ====================== 1. 生成正常飞行数据 ======================
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# 模拟几架真实飞机的ICAO地址
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normal_icaos = ["a1b2c3", "d4e5f6", "789abc", "def012"]
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base_time = 1656292550 # 起始时间戳
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for i in range(normal_count):
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icao = np.random.choice(normal_icaos)
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time = base_time + i * 2 # 每2秒一条数据
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# 正常的经纬度：缓慢变化
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lat = 40.0 + np.random.normal(0, 0.01) + (i * 0.001)
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lon = -90.0 + np.random.normal(0, 0.01) + (i * 0.001)
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# 正常的航向：0-360度，缓慢变化
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heading = 180 + np.random.normal(0, 5)
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# 正常的速度：200-300节
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velocity = 250 + np.random.normal(0, 10)
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# 正常的高度：10000米左右
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baroaltitude = 10000 + np.random.normal(0, 50)
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geoaltitude = baroaltitude + 100 + np.random.normal(0, 20)
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label = 0 # 正常
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data.append([icao, time, lat, lon, heading, velocity, baroaltitude, geoaltitude, label])
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# ====================== 2. 生成攻击数据 ======================
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attack_icaos = ["fake01", "ghost02", "attack03"]
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for i in range(attack_count):
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icao = np.random.choice(attack_icaos)
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time = base_time + (normal_count + i) * 2
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# 随机选择一种攻击类型
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attack_type = np.random.choice(["speed", "altitude", "position", "ghost"])
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if attack_type == "speed":
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# 攻击1：速度异常（突然变得极快或极慢）
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lat = 40.0 + np.random.normal(0, 0.01)
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lon = -90.0 + np.random.normal(0, 0.01)
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heading = 180
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velocity = np.random.choice([50, 500]) # 要么极慢，要么极快
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baroaltitude = 10000
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geoaltitude = 10100
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elif attack_type == "altitude":
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# 攻击2：高度异常（突然跳到0或极高）
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lat = 40.0 + np.random.normal(0, 0.01)
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lon = -90.0 + np.random.normal(0, 0.01)
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heading = 180
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velocity = 250
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baroaltitude = np.random.choice([0, 20000]) # 要么0，要么2万米
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geoaltitude = baroaltitude
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elif attack_type == "position":
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# 攻击3：位置异常（经纬度突然跳变）
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lat = np.random.uniform(-90, 90) # 随机全球位置
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lon = np.random.uniform(-180, 180)
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heading = 180
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velocity = 250
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baroaltitude = 10000
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geoaltitude = 10100
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else:
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# 攻击4：幽灵飞机（所有参数都不合理）
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lat = 0.0
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lon = 0.0
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heading = 999 # 不合理的航向
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velocity = 1000 # 超音速
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baroaltitude = 50000 # 不可能的高度
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geoaltitude = 50000
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label = 1 # 攻击
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data.append([icao, time, lat, lon, heading, velocity, baroaltitude, geoaltitude, label])
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# ====================== 3. 打乱并保存 ======================
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df = pd.DataFrame(data, columns=[
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"icao24", "time", "lat", "lon", "heading",
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"velocity", "baroaltitude", "geoaltitude", "label"
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])
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# 打乱顺序，让正常和攻击混在一起
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df = df.sample(frac=1).reset_index(drop=True)
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# 保存为CSV
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output_file = "test_adsb_data.csv"
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df.to_csv(output_file, index=False)
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print(f"✅ 测试数据生成成功！")
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print(f" 文件：{output_file}")
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print(f" 总数据：{len(df)} 条")
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print(f" 正常数据：{len(df[df['label']==0])} 条")
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print(f" 攻击数据：{len(df[df['label']==1])} 条")
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print(f"\n现在你可以上传 {output_file} 到你的系统测试了！")
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if __name__ == "__main__":
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generate_adsb_test_data(normal_count=120, attack_count=80) |
