Emerging New Trends in Hybrid Vehicle Localization Systems - Global Navigation Satellite Systems: Signal,Theory and Applications - page 294

The primary localization layer

IMU 2

IMU 1 IMU n

The estimate fusion and management layer

Fig. 7. Integrity monitoring layer.

and/or the signal to noise ratio can be utilized when a GPS receiver is used, light intensity
can be utilized when vision features are used, and KF innovation can be utilized when IVCAL
is used. Various tools can be employed in this layer based on the type of the localization
technique. Fuzzy inference systems and probabilistic models for reliability are two examples
of these tools.

9.3 The Estimate Fusion and Management Layer

The Estimate Fusion and Management layer (EFM) is responsible for determining an effective
integration (Meta-Fusion) strategy for fusing the estimates produced by the different primary
localization units so as to achieve the required localization accuracy and integrity (Figure
8). The estimate fusion and management processes the location estimates produced by the

Application

GPS INS

MAPs

Query (QoS)

Response

PLU n

PLU 1 PLU 2

Localization
Request

Estimate
Fusion and
Management

Calibration

IMU 1 IMU 2 IMU n

Ȧ i

z i

Fusion Layer

Fig. 8. Estimate fusion and management layer.

different primary localization units in conjunction with their integrity assessments. Since
the vehicle is expected to be performing localization while moving, it is imperative for the
fusion process to perform spatial and temporal alignment of the estimates produced by the
different PLUs. Therefore, this layer employs a synchronization handler to manage timing
issues among the different PLUs. Given the task's target accuracy and integrity, as well as