一个新型的适应性坚固的立方卡尔曼波器,用于在模型不确定性和异常测量噪声下操纵目标跟踪
Xiangzhou Ye1,2,3, Jian Wang1,2,3, Dongjie Wu1,2,3
1Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083, China.
Sensors (Basel, Switzerland)
|August 12, 2023
概括
这项研究引入了一种适应性强大的立方卡尔曼波器 (ARCKF),以提高雷达跟踪精度. 新型过器提高了对机动目标的稳定性和估计精度,优于传统方法.
科学领域:
- * * 信号处理 信号处理
- * 估计理论 * 估计理论
- * 控制系统工程 * 控制系统工程
背景情况:
- * 雷达追踪系统面临着对机动目标的挑战,其特点是高不确定性和非高斯噪声,阻碍了准确的估计.
- * 在过器设计中,在过器的强度和估计准确性之间取得平衡是持续存在的挑战.
- * H-infinity过器是一个公认的强大的算法,但其与立方卡尔曼过器 (CKF) 的集成需要进一步改进.
研究的目的:
- * 开发一种新的自适应性强立方卡尔曼波器 (ARCKF),可以改进H-无限立方卡尔曼波器 (HCKF).
- * 为了解决在操纵目标场景中的模型不确定性,并通过适应性估计测量噪声协差.
- * 为了提高雷达跟踪过器的稳定性和估计精度.
主要方法:
- * 提出了一个自适应性强立方卡尔曼波器 (ARCKF),建立在H-无限立方卡尔曼波器 (HCKF) 上.
- * 整合了自适应色因子,以减轻因目标机动而产生的模型不确定性.
- * 实施了使用Mahalanobis距离 (MD) 来进行自适应测量噪声共差估计的改进的Sage-Husa估计.
主要成果:
- *与标准HCKF相比,ARCKF在稳定性和估计精度方面取得了显著的改进.
- *模拟结果验证了ARCKF在管理系统模型错误方面的卓越性能.
- * 拟议的算法有效处理异常观测,优于传统的HCKF.
结论:
- *新型ARCKF有效地平衡了雷达跟踪中的稳定性和估计准确性.
- * 适应性组件成功地应对机动目标和测量噪声所带来的挑战.
- * ARCKF为在不确定和噪音条件下的雷达跟踪提供了更有效的解决方案.
相关概念视频
Propagation of Uncertainty from Systematic Error
554
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
554
Propagation of Uncertainty from Random Error
726
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
726
Relative Motion Analysis using Rotating Axes-Problem Solving
421
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
Here, in order to determine the magnitude of velocity and acceleration for point...
421
Uncertainty in Measurement: Accuracy and Precision
73.9K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
73.9K
Pole and System Stability
329
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
329
Calibration Curves: Linear Least Squares
1.4K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
For data that follow a straight line, the standard method for fitting is the linear...
1.4K


