1, The full form of PDAF is Phase-Detection AutoFocus. It’s used on Technology ,General in Worldwide

The phase-detection/AF system is a very complex system that sees improvements pretty much every time when a higher-end camera line is refreshed. Over the years, the number of autofocus points have been increasing, as well as the number of more reliable cross-type autofocus points.

2, The full form of PDAF is Priority Development Assistance Fund. It’s used on Governmental ,Politics in Philippines

The Priority Development Assistance Fund (PDAF) is a discretionary fund that allowed senators and congressmen to allot funds for their pet projects after the enactment of the budget law. It was controversial because the PDAF, a lump-sum budgetary item and a pork barrel, had been a source of kickbacks of lawmakers.

3, The full form of PDAF is Probabilistic Data Association Filter. It’s used on Technology ,General in Worldwide

The Probabilistic Data Association Filter (PDAF) is a statistical approach to the problem of plot association (target-measurement assignment) in a target tracking algorithm. Rather than choosing the most likely assignment of measurements to a target (or declaring the target not detected or a measurement to be a false alarm), the PDAF takes an expected value, which is the minimum mean square error (MMSE) estimate.

4, The full form of PDAF is Parallel Data Assimilation Framework. It’s used on Computing ,General Computing in Worldwide

The Parallel Data Assimilation Framework – PDAF – is a software environment for ensemble data assimilation. PDAF simplifies the implementation of the data assimilation system with existing numerical models. With this, users can obtain a data assimilation system with less work and can focus on applying data assimilation.

PDAF provides fully implemented and optimized data assimilation algorithms, in particular ensemble-based Kalman filters like LETKF and LESTKF and nonlinear filters. It allows users to easily test different assimilation algorithms and observations. PDAF is optimized for the application with large-scale models that usually run on big parallel computers and is applicable for operational applications. However, it is also well suited for smaller models and even toy models and can be used to teach data assimilation.

PDAF provides a standardized interface that separates the numerical model from the assimilation routines. This allows to perform the further development of the assimilation methods and the model independently. PDAF makes new algorithmic developments readily available through the interface such that they can be immediately applied with existing implementations. The PDAF release package provides small models for easy testing of algorithmic developments and for teaching data assimilation.

PDAF is a community open-source project. Its functionality will be further extended by input from research projects. In addition, users are welcome to contribute to the further enhancement of PDAF, e.g. by contributing additional assimilation methods or interface routines for different numerical models.