Launch point estimation with a single fixed passive sensor without trajectory state estimation

2021 ◽  
Author(s):  
Zijiao Tian ◽  
Kaipei Yang ◽  
Meir Danino ◽  
Yaakov Bar-Shalom ◽  
Benny Milgrom
Keyword(s):  
State Estimation ◽  
Point Estimation ◽  
Passive Sensor

Launch Point Estimation with a Single Passive Sensor Without Trajectory State Estimation

2021 ◽  
pp. 1-1
Author(s):  
Zijiao Tian ◽  
Kaipei Yang ◽  
Meir Danino ◽  
Yaakov Bar-Shalom ◽  
Benny Milgrom
Keyword(s):  
State Estimation ◽  
Point Estimation ◽  
Passive Sensor

Pursuer Aim Identification for an Aircraft Formation Using a Passive Sensor Without State Estimation

2021 ◽  
pp. 1-1
Author(s):  
Zijiao Tian ◽  
Kaipei Yang ◽  
Meir Danino ◽  
Yaakov Bar-Shalom ◽  
Benny Milgrom
Keyword(s):  
State Estimation ◽  
Passive Sensor

Development of State Estimation Filter Simulator Built on an Integrated GUI Framework

2016 ◽  
Vol 20 (5) ◽  
pp. 721-729
Author(s):  
Masaru Morita ◽  
◽  
Takeshi Nishida
Keyword(s):  
Time Series ◽  
User Interface ◽  
State Estimation ◽  
Graphical User Interface ◽  
Kalman Filters ◽  
Point Estimation ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
System Designer ◽  
The Relationship

We have developed a graphical user interface (GUI)-based state estimation filter simulator (called StefAny) that makes it easy to understand and compare the behaviors of filters such as Kalman filters (KFs) and particle filters (PFs). The key feature of StefAny is to show, when a system designer applies a PF, a detailed graph representing the relationship among the distribution and weights of all particles on any arbitrary timeline through simulation. Moreover, the timeline can be specified on another graph showing an estimated time series for each filter. These features enable system designers to easily check the compatibility between a filter and a target distribution, which determines the state estimation accuracy. In this paper, we present the functions of StefAny and demonstrate in detail how StefAny facilitates understanding of the properties of filters via a compatibility check comparison experiment for PFs, point estimation methods, and distributions.

Sign in / Sign up

Export Citation Format

Share Document