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A novel Kalman filter-based navigation using beacons

机译：使用信标的新型基于卡尔曼滤波器的导航

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摘要

A novel Kalman filter-based scheme is proposed to estimate the navigational states of a vehicle from the range measurements obtained using beacons (transmitter-receivers): at least three placed at known locations and one on the vehicle. The novelty of the scheme stems from 1) the use of pseudomeasurements which are some nonlinear function of the range measurements so that the measurement model is linear with the resulting Kalman filter globally convergent, 2) the measurements of the pair-wise sums and differences in the ranges so as to reduce the sensitivity to the measurement noise, and 3) the optimal location of the beacons to ensure that the state estimation error is minimised, resulting in the estimation accuracy being linear in the true states. Both the bias and the random errors are considered to account for the sources of errors such as the sensor bias, the faults, and the sensor noise. The proposed scheme is evaluated on a number of simulated examples
机译：提出了一种新颖的基于卡尔曼滤波器的方案，该方案从使用信标（发射器-接收器）获得的距离测量值估计车辆的导航状态：至少三个放置在已知位置，一个放置在车辆上。该方案的新颖性源于1）使用伪测量，伪测量是距离测量的某些非线性函数，因此测量模型与最终收敛的Kalman滤波器呈线性线性关系； 2）对和和的成对测量范围以减少对测量噪声的敏感度； 3）信标的最佳位置，以确保状态估计误差最小，从而在真实状态下估计精度呈线性。偏置和随机误差都被认为是造成误差源的原因，例如传感器偏置，故障和传感器噪声。在许多模拟实例上评估了所提出的方案

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