An Improved Method for Multi-Target Tracking

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An Improved Nearest Neighbor Data Association Method for Underwater Multi-Target Tracking

Nearest Neighbor (NN) data association method is the most popular and widely used algorithm for target tracking in the presence of clutter, due to its acceptable performance and low computational complexity. Despite of the good performance of this algorithm in single target tracking and even Multi-Target Tracking (MTT) with non-crossing paths scenarios, its performance degrades significantly in...

متن کامل

Multi-Target Tracking Using an Improved Gaussian Mixture CPHD Filter

The cardinalized probability hypothesis density (CPHD) filter is an alternative approximation to the full multi-target Bayesian filter for tracking multiple targets. However, although the joint propagation of the posterior intensity and cardinality distribution in its recursion allows more reliable estimates of the target number than the PHD filter, the CPHD filter suffers from the spooky effec...

متن کامل

Improved assignment with ant colony optimization for multi-target tracking

Detecting and tracking ground targets is crucial in military intelligence in battlefield surveillance. Once targets have been detected, the system used can proceed to track them where tracking can be done using Ground Moving Target Indicator (GMTI) type indicators that can observe objects moving in the area of interest. However, when targets move close to each other in formation as a convoy, th...

متن کامل

Improved Gaussian Mixture PHD Smoother for Multi-target Tracking

The Gaussian mixture probability hypothesis density (GM-PHD) smoother proposed recently can yield better state estimates than the GM-PHD filter. However, there are two major problems with it. First, the smoothed PHD distribution can not provide a more accurate target number estimate due to the target number estimation bias becoming larger by smoothing. Second, the computational complexity of co...

متن کامل

Improved Bearings-Only Multi-Target Tracking with GM-PHD Filtering

In this paper, an improved nonlinear Gaussian mixture probability hypothesis density (GM-PHD) filter is proposed to address bearings-only measurements in multi-target tracking. The proposed method, called the Gaussian mixture measurements-probability hypothesis density (GMM-PHD) filter, not only approximates the posterior intensity using a Gaussian mixture, but also models the likelihood functi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Information Technology Journal

سال: 2007

ISSN: 1812-5638

DOI: 10.3923/itj.2007.725.732