A fast method for finding the exact N-best hypotheses for multitarget tracking

Danchick R.; Newnam G.E.

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A fast method for finding the exact N-best hypotheses for multitarget tracking

机译：快速找到用于多目标跟踪的精确N最佳假设的方法

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The necessity for multiple hypothesis tracking (MHT) is recognized throughout the SDI tracking community. However, implementations of MHT techniques have required enormous amounts of computer time and memory. An efficient method of measurement-to-target association that makes MHT practical for the first time is presented. The method finds the exact N-best feasible hypotheses directly from a sequence of linear assignment problem solutions.

机译：整个SDI跟踪社区都认识到了进行多重假设跟踪（MHT）的必要性。但是，MHT技术的实现需要大量的计算机时间和内存。提出了一种使MHT首次实用的有效的测量与目标关联方法。该方法直接从一系列线性分配问题解决方案中找到确切的N最佳可行假设。

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《IEEE Transactions on Aerospace and Electronic Systems》 |1993年第2期|P.555-560|共6页
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Danchick R.; Newnam G.E.;
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正文语种 eng
中图分类航空;
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1. MULTITARGET STATE AND TRACK ESTIMATION FOR THE PROBABILITY HYPOTHESES DENSITY FILTER [J] . Liu Weifeng, Han Chongzhao, Lian Feng, 电子科学学刊（英文版） . 2009,第001期

机译：概率假设密度滤波的多目标状态和轨迹估计
2. MULTITARGET STATE AND TRACK ESTIMATION FOR THE PROBABILITY HYPOTHESES DENSITY FILTER [J] . Liu Weifeng, Han Chongzhao, Lian Feng, 电子科学学刊：英文版 . 2009,第001期

机译：概率假设密度滤波的多目标状态和轨迹估计
3. On finding ranked assignments with application to multitarget tracking and motion correspondence [J] . Cox I.J., Miller M.L. IEEE Transactions on Aerospace and Electronic Systems . 1995,第1期

机译：在找到排序的分配并应用于多目标跟踪和运动对应时
4. The N-best algorithms: an efficient and exact procedure for finding the N most likely sentence hypotheses [C] . Schwartz, R., Chow, . 1990

机译：N个最佳算法：找到N个最有可能的句子假设的有效且精确的过程
5. Advanced data fusion methods with application to the multitarget multisensor tracking problem. [D] . Nabaa, Nassib. 1997

机译：先进的数据融合方法及其在多目标多传感器跟踪问题中的应用。
6. Multiple Target Tracking Based on Multiple Hypotheses Tracking and Modified Ensemble Kalman Filter in Multi-Sensor Fusion [O] . Zequn Zhang, Kun Fu, Xian Sun, 2019

机译：基于多假设跟踪和改进的集成卡尔曼滤波的多传感器融合多目标跟踪
7. On MCMC-Based Particle Methods for Bayesian Filtering : Application to Multitarget Tracking [O] . Septier François, Pang Sze Kim, Carmi Avishy, 2009

机译：基于贝叶斯滤波的基于MCMC的粒子方法：在多目标跟踪中的应用
8. Representing and Scoring Track Hypotheses for Multitarget groups. [R] . Hastings, C. H., Withers, L. P., DeWitt, R. N. 1998

机译：多目标组的代表和评分跟踪假设。

A fast method for finding the exact N-best hypotheses for multitarget tracking

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