Search - DATA ASSOCIATION AND TRACKING

Search - DATA ASSOCIATION AND TRACKING - List

[Other] PDA DL : 0: 数据关联算法－PDA算法，能有效的跟踪目标-data association algorithm-PDA algorithm can effectively target tracking
Date : 2025-12-23 Size : 3kb User : fengyang
[Other] IMMPDA DL : 0: 多模型和概率数据关联结合后的IMMPDA算法，主要用于雷达数据处理，单目标的在杂波环境下的目标跟踪。-Multi-model and probabilistic data association after combining IMMPDA algorithm, mainly used for radar data processing, a single goal in the cluttered environment of the target tracking.
Date : 2025-12-23 Size : 4kb User : lgvee
[Other] 153_PMHT_Problems_and_Somesolutions DL : 0: PMHT是一个优秀的跟踪算法，具有灵活性和易修正的特点。-The probabilistic multihypothesis tracker (PMHT) is a target tracking algorithm of considerable theoretical elegance. In practice, its performance turns out to be at best similar to that of the probabilistic data association filter (PDAF) and since the implementation of the PDAF is less intense numerically the PMHT has been having a hard time finding acceptance. The PMHT’s problems of nonadaptivity, narcissism, and over-hospitality to clutter are elicited in this work. The PMHT’s main selling-point is its flexible and easily modifiable model, which we use to develop the “homothetic” PMHT maneuver-based PMHTs, including those with separate and joint homothetic measurement models a modified PMHT whose measurement/target association model is more similar to that of the PDAF and PMHTs with eccentric and/or estimated measurement models.
Date : 2025-12-23 Size : 429kb User : wang zhuo
[Other] IMM DL : 0: （交互式多模型算法）目标跟踪程序,java语言编写，包含了kalman滤波。这种方法的特点是在各模型之间“转换”，自动调节滤波带宽，和适合机动目标的跟踪。可以直接调用，附有示例代码-A multi-target tracking toolbox based on the MTT Library of the InstantVision ISE with expanded functionality and tools for off-line design, analysis and testing. The toolbox contains the implementation of distance calculation methods (e.g. city-block based), data assignment and association strategies (e.g. ENN and JVC), state prediction filters (e.g. IMM) with video marking and debugging tools in order to support a complex multi-target tracking system design.
Date : 2025-12-23 Size : 14kb User : june
[Other] JPDA DL : 0: 在运动的位置叠加噪声。进行JPDA概率数据关联及kalman滤波。两运动目标在x-y平面做匀速直线运动。初始位置是（4000,1200）（300,1500）速度分别是（200,200）（400,200）传感器对量目标进行位置状态量测。采样间隔T=1,点数n=80.检测概率为1，正确量测落入跟踪内的概率为0.99，杂波均匀分布的密度为2个/km2由RAND函数产生在[0，1]上均匀分布的随机变量，跟踪门限为9.21。 -Superimposed noise in the position of the movement. JPDA probabilistic data association and kalman filtering. Two moving targets uniform linear motion in the xy plane. The initial position (4000,1200) (300,1500) speed (200,200) (400,200) position sensor on the amount of target state measurements. Sampling interval T = 1, points n = 80. Detection probability of correctly measured fall into the tracking probability 0.99, 2/km2 clutter uniform distribution of density generated by the RAND function [0,1] uniformly distributed random variables tracking threshold of 9.21.
Date : 2025-12-23 Size : 3kb User : 雪
[Other] Target-Tracking-PADF3 DL : 0: 仅供参考，采用数据关联算法实现单个匀速运动目标的点迹与航迹的关联；PDAF方法第三种实现；-For reference only, using a single data association algorithm uniform motion targets associated trace and track the point PDAF third method to achieve
Date : 2025-12-23 Size : 3kb User : yang