航空関連ソフトウェア¶

// Flightradar24 API使用例（非公式）
interface FlightData {
  flight_id: string;
  callsign: string;
  latitude: number;
  longitude: number;
  altitude: number;
  speed: number;
  heading: number;
  aircraft_type: string;
}

class FlightTracker {
  async getFlightsInBounds(
    north: number, 
    south: number, 
    east: number, 
    west: number
  ): Promise<FlightData[]> {
    const response = await fetch(
      `https://data-cloud.flightradar24.com/zones/fcgi/feed.js?bounds=${north},${south},${east},${west}`
    );
    return response.json();
  }
}

// OpenSky Network API例（オープンソース）
interface StateVector {
  icao24: string;
  callsign: string;
  origin_country: string;
  time_position: number;
  last_contact: number;
  longitude: number;
  latitude: number;
  baro_altitude: number;
  on_ground: boolean;
  velocity: number;
  true_track: number;
  vertical_rate: number;
}

class OpenSkyClient {
  private readonly baseUrl = 'https://opensky-network.org/api';

  async getAllStates(): Promise<StateVector[]> {
    const response = await fetch(`${this.baseUrl}/states/all`);
    const data = await response.json();
    return data.states.map(this.parseStateVector);
  }

  private parseStateVector(state: any[]): StateVector {
    return {
      icao24: state[0],
      callsign: state[1]?.trim() || null,
      origin_country: state[2],
      time_position: state[3],
      last_contact: state[4],
      longitude: state[5],
      latitude: state[6],
      baro_altitude: state[7],
      on_ground: state[8],
      velocity: state[9],
      true_track: state[10],
      vertical_rate: state[11]
    };
  }
}

// レーダーデータ処理の基本構造
interface RadarContact {
  id: string;
  position: {
    latitude: number;
    longitude: number;
    altitude: number;
  };
  velocity: {
    speed: number;
    heading: number;
    vertical_rate: number;
  };
  identification: {
    callsign?: string;
    squawk: string;
    aircraft_type?: string;
  };
  timestamp: Date;
  confidence: number;
}

class RadarProcessor {
  private contacts = new Map<string, RadarContact[]>();

  // 複数レーダーからのデータ統合
  fuseRadarData(radarSources: RadarContact[][]): RadarContact[] {
    const fusedData: RadarContact[] = [];

    // 位置ベースでの相関処理
    for (const contact of radarSources.flat()) {
      const existing = fusedData.find(c => 
        this.calculateDistance(c.position, contact.position) < 0.1 // 100m以内
      );

      if (existing) {
        // 信頼度の高いデータで更新
        if (contact.confidence > existing.confidence) {
          Object.assign(existing, contact);
        }
      } else {
        fusedData.push(contact);
      }
    }

    return fusedData;
  }

  // 軌道予測
  predictTrajectory(contact: RadarContact, timeAhead: number): Position {
    const { latitude, longitude, altitude } = contact.position;
    const { speed, heading, vertical_rate } = contact.velocity;

    // 簡単な線形予測（実際はより複雑な計算）
    const distance = speed * timeAhead;
    const deltaLat = (distance * Math.cos(heading * Math.PI / 180)) / 111000;
    const deltaLng = (distance * Math.sin(heading * Math.PI / 180)) / (111000 * Math.cos(latitude * Math.PI / 180));

    return {
      latitude: latitude + deltaLat,
      longitude: longitude + deltaLng,
      altitude: altitude + (vertical_rate * timeAhead)
    };
  }
}

// TCAS アルゴリズムの簡単な実装例
class TCASProcessor {
  private readonly ALERT_LEVELS = {
    TRAFFIC_ADVISORY: 1,
    RESOLUTION_ADVISORY: 2
  };

  assessThreat(ownship: RadarContact, intruder: RadarContact): TCASAlert | null {
    const separation = this.calculateSeparation(ownship, intruder);
    const closestPointOfApproach = this.calculateCPA(ownship, intruder);

    if (this.isImmediateThreat(separation, closestPointOfApproach)) {
      return {
        level: this.ALERT_LEVELS.RESOLUTION_ADVISORY,
        type: 'vertical', // climb/descend
        intruderCallsign: intruder.identification.callsign,
        recommendedAction: this.generateResolutionAdvisory(ownship, intruder)
      };
    } else if (this.isPotentialThreat(separation, closestPointOfApproach)) {
      return {
        level: this.ALERT_LEVELS.TRAFFIC_ADVISORY,
        type: 'advisory',
        intruderCallsign: intruder.identification.callsign,
        recommendedAction: 'monitor'
      };
    }

    return null;
  }

  private generateResolutionAdvisory(ownship: RadarContact, intruder: RadarContact): string {
    // 相対的な垂直速度を計算
    const relativeVerticalRate = ownship.velocity.vertical_rate - intruder.velocity.vertical_rate;

    if (relativeVerticalRate > 0) {
      return 'DESCEND'; // 自機が上昇中なら降下指示
    } else {
      return 'CLIMB';   // 自機が降下中なら上昇指示
    }
  }
}

interface TCASAlert {
  level: number;
  type: string;
  intruderCallsign?: string;
  recommendedAction: string;
}

// 航空気象情報の統合システム
interface WeatherData {
  timestamp: Date;
  location: {
    latitude: number;
    longitude: number;
    altitude?: number;
  };
  visibility: number;        // km
  windSpeed: number;         // knots
  windDirection: number;     // degrees
  temperature: number;       // Celsius
  dewPoint: number;          // Celsius
  pressure: number;          // hPa
  cloudLayers: CloudLayer[];
  precipitation?: PrecipitationType;
  turbulence?: TurbulenceLevel;
}

interface CloudLayer {
  type: 'FEW' | 'SCT' | 'BKN' | 'OVC';
  altitude: number; // feet
  thickness?: number;
}

class AviationWeatherService {
  private readonly sources = {
    metar: 'https://aviationweather.gov/adds/dataserver_current/httpparam?dataSource=metars',
    taf: 'https://aviationweather.gov/adds/dataserver_current/httpparam?dataSource=tafs',
    radar: 'https://aviationweather.gov/adds/dataserver_current/httpparam?dataSource=radars'
  };

  async getCurrentWeather(airportCode: string): Promise<WeatherData> {
    const metarUrl = `${this.sources.metar}&requestType=retrieve&format=xml&stationString=${airportCode}&hoursBeforeNow=1`;
    const response = await fetch(metarUrl);
    const xmlData = await response.text();

    return this.parseMetar(xmlData);
  }

  async getWeatherForecast(airportCode: string): Promise<WeatherData[]> {
    const tafUrl = `${this.sources.taf}&requestType=retrieve&format=xml&stationString=${airportCode}&hoursBeforeNow=4&timeType=issue`;
    const response = await fetch(tafUrl);
    const xmlData = await response.text();

    return this.parseTaf(xmlData);
  }

  // 乱気流予測
  async getTurbulenceForecast(
    bounds: { north: number; south: number; east: number; west: number },
    altitudes: number[]
  ): Promise<TurbulenceForecast[]> {
    // 複数の気象モデルからデータを収集
    const gfsData = await this.getGFSData(bounds, altitudes);
    const ecmwfData = await this.getECMWFData(bounds, altitudes);

    // アンサンブル予測
    return this.generateTurbulenceEnsemble(gfsData, ecmwfData);
  }
}

// 機上気象レーダーデータの統合
class OnboardWeatherRadar {
  private canvas: HTMLCanvasElement;
  private context: CanvasRenderingContext2D;

  constructor(canvasElement: HTMLCanvasElement) {
    this.canvas = canvasElement;
    this.context = canvasElement.getContext('2d')!;
  }

  renderWeatherData(radarData: WeatherRadarData): void {
    this.context.clearRect(0, 0, this.canvas.width, this.canvas.height);

    // 降水強度に基づく色分け
    const colorMap = {
      light: '#00FF00',      // 緑：弱い雨
      moderate: '#FFFF00',   // 黄：中程度の雨
      heavy: '#FF8000',      // オレンジ：強い雨
      severe: '#FF0000',     // 赤：激しい雨
      extreme: '#FF00FF'     // マゼンタ：極端に激しい雨
    };

    for (const cell of radarData.cells) {
      this.context.fillStyle = colorMap[cell.intensity];
      this.context.fillRect(
        cell.x - cell.width / 2,
        cell.y - cell.height / 2,
        cell.width,
        cell.height
      );
    }

    // パイロットへの推奨ルート表示
    this.renderRecommendedPath(radarData.recommendedPath);
  }

  private renderRecommendedPath(path: Point[]): void {
    if (path.length < 2) return;

    this.context.strokeStyle = '#00FFFF'; // シアン色
    this.context.lineWidth = 3;
    this.context.setLineDash([10, 5]);

    this.context.beginPath();
    this.context.moveTo(path[0].x, path[0].y);

    for (let i = 1; i < path.length; i++) {
      this.context.lineTo(path[i].x, path[i].y);
    }

    this.context.stroke();
    this.context.setLineDash([]); // リセット
  }
}

// X-Plane プラグイン例（概念的）
interface XPlaneDataRef {
  path: string;
  value: number | number[] | string;
  writable: boolean;
}

class XPlanePlugin {
  private datarefs: Map<string, XPlaneDataRef> = new Map();

  // データレファレンスの取得
  getDataref(path: string): number | number[] | null {
    const dataref = this.datarefs.get(path);
    return dataref ? dataref.value : null;
  }

  // 航空機状態の監視
  monitorAircraftState(): Observable<AircraftState> {
    return interval(100).pipe( // 10Hz更新
      map(() => ({
        position: {
          latitude: this.getDataref('sim/flightmodel/position/latitude') as number,
          longitude: this.getDataref('sim/flightmodel/position/longitude') as number,
          altitude: this.getDataref('sim/flightmodel/position/elevation') as number
        },
        attitude: {
          pitch: this.getDataref('sim/flightmodel/position/theta') as number,
          roll: this.getDataref('sim/flightmodel/position/phi') as number,
          heading: this.getDataref('sim/flightmodel/position/psi') as number
        },
        velocity: {
          groundSpeed: this.getDataref('sim/flightmodel/position/groundspeed') as number,
          indicatedAirspeed: this.getDataref('sim/flightmodel/position/indicated_airspeed') as number,
          verticalSpeed: this.getDataref('sim/flightmodel/position/vh_ind_fpm') as number
        },
        engine: {
          n1: this.getDataref('sim/flightmodel/engine/ENGN_N1_') as number[],
          egt: this.getDataref('sim/flightmodel/engine/ENGN_EGT_c') as number[],
          fuelFlow: this.getDataref('sim/flightmodel/engine/ENGN_FF_') as number[]
        }
      }))
    );
  }

  // 状況認識訓練シナリオ
  createSituationAwarenessScenario(): TrainingScenario {
    return {
      name: "Weather Avoidance Training",
      description: "Navigate around thunderstorms using onboard radar",
      objectives: [
        "Detect weather on radar",
        "Plan deviation route",
        "Execute safe weather avoidance",
        "Maintain situational awareness"
      ],
      initialConditions: {
        position: { lat: 35.0, lng: -97.0, alt: 35000 },
        weather: [
          {
            type: 'thunderstorm',
            position: { lat: 35.5, lng: -96.5 },
            radius: 10,
            intensity: 'severe'
          }
        ]
      },
      triggers: [
        {
          condition: 'distance_to_weather < 50nm',
          action: 'enable_weather_radar'
        },
        {
          condition: 'deviation_initiated',
          action: 'evaluate_decision_quality'
        }
      ]
    };
  }
}

interface AircraftState {
  position: { latitude: number; longitude: number; altitude: number };
  attitude: { pitch: number; roll: number; heading: number };
  velocity: { groundSpeed: number; indicatedAirspeed: number; verticalSpeed: number };
  engine: { n1: number[]; egt: number[]; fuelFlow: number[] };
}

interface TrainingScenario {
  name: string;
  description: string;
  objectives: string[];
  initialConditions: any;
  triggers: Array<{ condition: string; action: string }>;
}

// 空港運営の協調的意思決定システム
interface FlightMovement {
  flightId: string;
  callsign: string;
  aircraftType: string;
  origin?: string;
  destination?: string;
  scheduleTime: Date;
  estimatedTime: Date;
  actualTime?: Date;
  gate?: string;
  stand?: string;
  runway?: string;
  status: FlightStatus;
}

type FlightStatus = 
  | 'scheduled' 
  | 'delayed' 
  | 'boarding' 
  | 'departed' 
  | 'arrived' 
  | 'cancelled';

class ACDMSystem {
  private flights = new Map<string, FlightMovement>();
  private airport: AirportConfig;

  constructor(airportConfig: AirportConfig) {
    this.airport = airportConfig;
  }

  // 出発時刻の予測と最適化
  calculateOptimalDepartureTimes(): Map<string, Date> {
    const sortedFlights = Array.from(this.flights.values())
      .filter(f => f.status === 'scheduled')
      .sort((a, b) => a.scheduleTime.getTime() - b.scheduleTime.getTime());

    const optimizedTimes = new Map<string, Date>();
    let lastDepartureTime = new Date();

    for (const flight of sortedFlights) {
      // 最小間隔の確保（航跡乱気流等を考慮）
      const minSeparation = this.calculateMinSeparation(flight);
      const earliestDeparture = new Date(lastDepartureTime.getTime() + minSeparation * 1000);

      // スケジュールとの比較
      const optimalTime = new Date(Math.max(
        flight.scheduleTime.getTime(),
        earliestDeparture.getTime()
      ));

      optimizedTimes.set(flight.flightId, optimalTime);
      lastDepartureTime = optimalTime;
    }

    return optimizedTimes;
  }

  // リソース競合の解決
  resolveResourceConflicts(): ResourceAllocation[] {
    const allocations: ResourceAllocation[] = [];
    const gateUsage = new Map<string, TimeSlot[]>();
    const runwayUsage = new Map<string, TimeSlot[]>();

    // ゲート割り当ての最適化
    for (const flight of this.flights.values()) {
      const preferredGate = this.findPreferredGate(flight);
      const availableSlot = this.findAvailableSlot(gateUsage, preferredGate, flight);

      if (availableSlot) {
        allocations.push({
          flightId: flight.flightId,
          resourceType: 'gate',
          resourceId: preferredGate,
          timeSlot: availableSlot
        });

        this.addTimeSlot(gateUsage, preferredGate, availableSlot);
      }
    }

    return allocations;
  }

  // ターンアラウンド時間の最適化
  optimizeTurnaround(flight: FlightMovement): TurnaroundPlan {
    const services = [
      { name: 'refueling', duration: 20, canParallel: true },
      { name: 'catering', duration: 30, canParallel: true },
      { name: 'cleaning', duration: 25, canParallel: false },
      { name: 'maintenance', duration: 15, canParallel: true },
      { name: 'baggage', duration: 35, canParallel: true }
    ];

    // 並行処理可能なサービスをグループ化
    const parallelServices = services.filter(s => s.canParallel);
    const sequentialServices = services.filter(s => !s.canParallel);

    // 最適なスケジューリング
    const plan: TurnaroundPlan = {
      flightId: flight.flightId,
      totalDuration: Math.max(
        Math.max(...parallelServices.map(s => s.duration)),
        sequentialServices.reduce((sum, s) => sum + s.duration, 0)
      ),
      schedule: this.createServiceSchedule(services, flight.actualTime || flight.estimatedTime)
    };

    return plan;
  }
}

interface AirportConfig {
  code: string;
  runways: Runway[];
  gates: Gate[];
  stands: Stand[];
}

interface ResourceAllocation {
  flightId: string;
  resourceType: 'gate' | 'runway' | 'stand';
  resourceId: string;
  timeSlot: TimeSlot;
}

interface TimeSlot {
  start: Date;
  end: Date;
}

interface TurnaroundPlan {
  flightId: string;
  totalDuration: number; // minutes
  schedule: ServiceSchedule[];
}

interface ServiceSchedule {
  service: string;
  start: Date;
  duration: number;
}

// 4D航法システムの概念実装
interface FourDTrajectory {
  waypoints: Array<{
    position: { lat: number; lng: number; alt: number };
    timeConstraint: Date;
    speedConstraint?: number;
  }>;
  uncertaintyEnvelope: {
    lateral: number;    // nautical miles
    vertical: number;   // feet
    temporal: number;   // seconds
  };
  performance: {
    fuel: number;       // kg
    emissions: number;  // kg CO2
    noise: number;      // dB
  };
}

class FourDNavigationSystem {
  calculateOptimalTrajectory(
    origin: Waypoint,
    destination: Waypoint,
    constraints: FlightConstraints,
    weatherData: WeatherData[],
    trafficDensity: TrafficDensity[]
  ): FourDTrajectory {
    // 多目的最適化（燃費、時間、環境）
    const costFunction = this.createCostFunction(constraints);

    // 動的計画法による最適経路計算
    const optimalPath = this.dynamicProgramming(
      origin,
      destination,
      weatherData,
      trafficDensity,
      costFunction
    );

    // 不確実性の考慮
    const uncertaintyEnvelope = this.calculateUncertainty(
      optimalPath,
      weatherData,
      trafficDensity
    );

    return {
      waypoints: optimalPath,
      uncertaintyEnvelope,
      performance: this.calculatePerformance(optimalPath, weatherData)
    };
  }

  // リアルタイム軌道調整
  adjustTrajectoryInFlight(
    currentTrajectory: FourDTrajectory,
    currentPosition: Position,
    updatedConditions: {
      weather?: WeatherData[];
      traffic?: TrafficInfo[];
      constraints?: FlightConstraints;
    }
  ): FourDTrajectory {
    // 現在位置からの軌道再計算
    const remainingWaypoints = currentTrajectory.waypoints.filter(wp => 
      this.isAhead(currentPosition, wp.position)
    );

    // 新しい条件での最適化
    return this.calculateOptimalTrajectory(
      { position: currentPosition, time: new Date() },
      remainingWaypoints[remainingWaypoints.length - 1],
      updatedConditions.constraints || {},
      updatedConditions.weather || [],
      updatedConditions.traffic || []
    );
  }
}

// AI支援による航空交通管理
class AIAssistedATM {
  private model: TensorFlow.LayersModel;

  async loadModel(): Promise<void> {
    this.model = await tf.loadLayersModel('/models/atm-optimization.json');
  }

  // 交通渋滞予測
  predictCongestion(
    currentTraffic: TrafficSnapshot,
    weatherForecast: WeatherForecast[],
    flightSchedules: FlightSchedule[]
  ): Promise<CongestionPrediction> {
    // 入力データの正規化
    const normalizedInputs = this.normalizeInputs({
      traffic: currentTraffic,
      weather: weatherForecast,
      schedules: flightSchedules
    });

    // モデル推論
    const prediction = this.model.predict(normalizedInputs) as tf.Tensor;
    const predictionData = await prediction.data();

    return {
      sectors: this.parseSectorPredictions(predictionData),
      timeHorizon: 120, // minutes
      confidence: this.calculateConfidence(predictionData)
    };
  }

  // 最適な制限措置提案
  recommendFlowControl(
    congestionPrediction: CongestionPrediction,
    currentOperations: OperationalData
  ): FlowControlMeasures[] {
    const measures: FlowControlMeasures[] = [];

    for (const sector of congestionPrediction.sectors) {
      if (sector.congestionLevel > 0.7) {
        measures.push({
          type: 'ground_delay',
          affectedFlights: this.identifyAffectedFlights(sector),
          delayMinutes: this.calculateOptimalDelay(sector),
          expectedReduction: sector.congestionLevel * 0.3
        });
      }
    }

    return measures;
  }
}

interface CongestionPrediction {
  sectors: Array<{
    id: string;
    congestionLevel: number; // 0-1
    peakTime: Date;
    duration: number; // minutes
  }>;
  timeHorizon: number;
  confidence: number;
}

interface FlowControlMeasures {
  type: 'ground_delay' | 'airborne_holding' | 'route_diversion';
  affectedFlights: string[];
  delayMinutes?: number;
  expectedReduction: number;
}

// 航空システムのセキュリティ実装例
class AviationSecurityLayer {
  private encryptionKey: CryptoKey;
  private auditLogger: AuditLogger;

  // データ暗号化
  async encryptFlightData(data: FlightData): Promise<EncryptedData> {
    const encrypted = await window.crypto.subtle.encrypt(
      { name: 'AES-GCM', iv: crypto.getRandomValues(new Uint8Array(12)) },
      this.encryptionKey,
      new TextEncoder().encode(JSON.stringify(data))
    );

    this.auditLogger.log('data_encrypted', {
      flightId: data.flightId,
      timestamp: new Date()
    });

    return { data: encrypted, iv: encrypted.slice(0, 12) };
  }

  // アクセス制御
  validateAccess(user: User, resource: string, action: string): boolean {
    const userRoles = user.roles;
    const requiredPermissions = this.getRequiredPermissions(resource, action);

    const hasPermission = requiredPermissions.every(permission => 
      userRoles.some(role => role.permissions.includes(permission))
    );

    this.auditLogger.log('access_attempt', {
      userId: user.id,
      resource,
      action,
      granted: hasPermission,
      timestamp: new Date()
    });

    return hasPermission;
  }

  // リアルタイム脅威検知
  monitorAbnormalPatterns(): Observable<SecurityAlert> {
    return merge(
      this.monitorLoginPatterns(),
      this.monitorDataAccess(),
      this.monitorSystemPerformance()
    ).pipe(
      filter(event => this.isAbnormal(event)),
      map(event => this.createSecurityAlert(event))
    );
  }
}

// ICAO標準データフォーマット例
interface ICAOFlightPlan {
  // FPL message format
  messageType: 'FPL';
  aircraftIdentification: string;
  flightRules: 'I' | 'V' | 'Y' | 'Z'; // IFR/VFR
  typeOfFlight: 'S' | 'N' | 'G' | 'M' | 'X';
  equipment: {
    aircraft: string; // ICAO aircraft type designator
    wakeCategory: 'L' | 'M' | 'H' | 'J'; // Light/Medium/Heavy/Super
    transponder: string; // ICAO transponder codes
  };
  departure: {
    aerodrome: string; // ICAO airport code
    time: Date;
  };
  cruisingSpeed: string;
  cruisingLevel: string;
  route: string; // ICAO route format
  destination: {
    aerodrome: string;
    totalEET: string; // Estimated Elapsed Time
  };
  alternate?: {
    aerodrome1?: string;
    aerodrome2?: string;
  };
  otherInformation: string;
}

class ICAOMessageProcessor {
  // ICAO標準メッセージのパース
  parseFlightPlan(rawMessage: string): ICAOFlightPlan {
    const fields = rawMessage.split('-');

    return {
      messageType: 'FPL',
      aircraftIdentification: this.extractField(fields, 7),
      flightRules: this.extractField(fields, 8)[0] as any,
      typeOfFlight: this.extractField(fields, 8)[1] as any,
      equipment: this.parseEquipment(this.extractField(fields, 9)),
      departure: this.parseDeparture(this.extractField(fields, 13)),
      cruisingSpeed: this.extractCruisingSpeed(this.extractField(fields, 15)),
      cruisingLevel: this.extractCruisingLevel(this.extractField(fields, 15)),
      route: this.extractField(fields, 15).split('/').slice(1).join(' '),
      destination: this.parseDestination(this.extractField(fields, 16)),
      alternate: this.parseAlternate(this.extractField(fields, 16)),
      otherInformation: this.extractField(fields, 18)
    };
  }

  // AIXM (Aeronautical Information Exchange Model) 対応
  generateAIXMData(flightPlan: ICAOFlightPlan): string {
    const aixmTemplate = `
      <message:AIXMBasicMessage 
        xmlns:message="http://www.aixm.aero/schema/5.1/message"
        xmlns:gml="http://www.opengis.net/gml/3.2">
        <message:hasMember>
          <aixm:RouteSegment gml:id="${this.generateId()}">
            <aixm:timeSlice>
              <aixm:RouteSegmentTimeSlice gml:id="${this.generateId()}">
                <gml:validTime />
                <aixm:interpretation>BASELINE</aixm:interpretation>
                <aixm:start xlink:href="#${flightPlan.departure.aerodrome}" />
                <aixm:end xlink:href="#${flightPlan.destination.aerodrome}" />
                <aixm:route>${flightPlan.route}</aixm:route>
              </aixm:RouteSegmentTimeSlice>
            </aixm:timeSlice>
          </aixm:RouteSegment>
        </message:hasMember>
      </message:AIXMBasicMessage>
    `;

    return aixmTemplate.trim();
  }
}