CAJ | 학술논문

提出了一种利用两次卡尔曼滤波实现非视距环境中TDOA/AOA混合定位方法。根据类正态分布密度曲线是最小二乘意义下对指数分布密度曲线的最优拟合的思想建立TDOA误差模型，先利用卡尔曼滤波对TOA测量值进行预处理以消除NLOS误差，再把经过预处理的TOA测量值输入到卡尔曼滤波器来实现TDOA/AOA混合定位。仿真结果表明，该方法的定位误差性能明显优于单纯的TDOA定位方法以及服从指数分布误差模型下的TDOA定位方法。
제출료일충이용량차잡이만려파실현비시거배경중TDOA/AOA혼합정위방법。근거류정태분포밀도곡선시최소이승의의하대지수분포밀도곡선적최우의합적사상건립TDOA오차모형，선이용잡이만려파대TOA측량치진행예처리이소제NLOS오차，재파경과예처리적TOA측량치수입도잡이만려파기래실현TDOA/AOA혼합정위。방진결과표명，해방법적정위오차성능명현우우단순적TDOA정위방법이급복종지수분포오차모형하적TDOA정위방법。
A novel TDOA(Time-Difference-Of Arrival)/AOA(Angle-Of-Arrival) wireless position scheme in NLOS (Non-Line-Of-Sight)environment which uses two Kalman filters is proposed. According to a thought that the type of nor-mal distribution density curve is the optimal fitting for exponential distribution density curve in the least-squares sense, TDOA error model is established. First, a Kalman filter is used to preprocess the TOA(Time-Of Arrival)measurements for eliminating the NLOS errors. Then these preprocessed measurements are input to the TDOA/AOA hybrid location which uses another Kalman filter. The simulation results show that the method of positioning error is better than pure TDOA location method and the TDOA location which error is exponential distribution model.