A solution to the problem of sensor bias estimation is presented for a multiple target scenario with asynchronous sensors. Expectation maximisation is used to decouple the target state and sensor bias estimation problems by treating the target states as missing data. The approach is compared with the EX method, which solves the bias estimation problem by using differences between measurements from different sensors
In tracking applications, the target state (e.g., position, velocity) can be estimated by processing...
This article investigates the problem of estimating biases affecting relative state measurements in ...
This article investigates the problem of estimating biases affecting relative state measurements in ...
This paper provides the exact solution for the bias estimation problem in multiple asynchronous sens...
In this dissertation research, three topics in multisensor bias estimation are discussed: sensor bia...
In this dissertation research, three topics in multisensor bias estimation are discussed: sensor bia...
An important prerequisite for successful multisensor integration is that the data from the reporting...
This paper presents a sensor bias estimation method with serial fusion for asynchronous multisensory...
Most of the literature pertaining to target tracking assumes that the sensor data are corrupted by m...
Most of the literature pertaining to target tracking assumes that the sensor data are corrupted by m...
In the field of target tracking there are many challenges associated with error in sensor measuremen...
In the problem of target tracking, different types of biases can enter into the measurement collecte...
In the field of target tracking there are many challenges associated with error in sensor measuremen...
Multitarget detection and tracking algorithms typically presume that sensors are spatially registere...
In tracking applications, the target state (e.g, position, velocity) can be estimated by processing ...
In tracking applications, the target state (e.g., position, velocity) can be estimated by processing...
This article investigates the problem of estimating biases affecting relative state measurements in ...
This article investigates the problem of estimating biases affecting relative state measurements in ...
This paper provides the exact solution for the bias estimation problem in multiple asynchronous sens...
In this dissertation research, three topics in multisensor bias estimation are discussed: sensor bia...
In this dissertation research, three topics in multisensor bias estimation are discussed: sensor bia...
An important prerequisite for successful multisensor integration is that the data from the reporting...
This paper presents a sensor bias estimation method with serial fusion for asynchronous multisensory...
Most of the literature pertaining to target tracking assumes that the sensor data are corrupted by m...
Most of the literature pertaining to target tracking assumes that the sensor data are corrupted by m...
In the field of target tracking there are many challenges associated with error in sensor measuremen...
In the problem of target tracking, different types of biases can enter into the measurement collecte...
In the field of target tracking there are many challenges associated with error in sensor measuremen...
Multitarget detection and tracking algorithms typically presume that sensors are spatially registere...
In tracking applications, the target state (e.g, position, velocity) can be estimated by processing ...
In tracking applications, the target state (e.g., position, velocity) can be estimated by processing...
This article investigates the problem of estimating biases affecting relative state measurements in ...
This article investigates the problem of estimating biases affecting relative state measurements in ...