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时间:2011-09-14 15:44来源:蓝天飞行翻译 作者:航空
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In addition to performing the prescribed HVO procedures, pilots are also responsible for monitoring separation between aircraft in the SCA. The HVO procedures are designed such that if everything goes as planned, the aircraft will maintain separation. However, there is always the possibility for errors – someone may initiate their approach too soon, for example. In this case, onboard CD&A logic is expected to notify the pilot of the possible loss of separation. The NASA-defined CD&A algorithms include the concept of procedural conformance.9 In the HVO concept, each aircraft is required to have software that monitors its aircraft’s state to determine if it is conforming to the HVO procedures. The HVO requirements state that each aircraft broadcast a “conformance bit” in an extended ADS-B message. The inclusion of ownship conformance monitoring places a considerable design requirement on the HVO avionics – a design requirement that can be met by flight segment identification.
In Part III, we describe the details of our approach to flight segment identification, using HVO procedures as an example application.


Figure 5. Aircraft’s state diagram for High Volume Operations.

III. Flight Segment Identification
Flight Segment Identification (FSI) is the process of monitoring aircraft state variables and flight events to identify in real-time the phase of flight or operational procedure in which an aircraft is operating. FSI can be used to identify the phase of flight that the pilot is flying. FSI can also be used to identify the phase of flight that the pilot should be flying. One reason to implement FSI in avionics is to support the generation of pilot advisory messages, like those shown in Fig. 6. The messages may be textual, graphical, auditory, or even haptic. Regardless, pilot advisory systems need the context that FSI can provide. 
A. State-based FSI
If avionics has a requirement for identifying the flight segment, how might that be implemented? One approach is to include a button for the pilot to press or a knob for the pilot to turn to set the current flight segment. This approach to flight segment identification has the obvious drawbacks of increasing pilot workload and being error-prone. A preferred implementation would track the flight segments automatically without requiring pilot intervention.
If an FSI module should not rely on pilot input, then what is the basis for deciding what flight segment the pilot is currently flying? The decision is made based on the aircraft state

variables – position relative to the flight plan, altitude, airspeed, vertical speed, etc. We have termed this decision state-based flight segment interpretation (S-FSI). In contrast to the procedural FSI described in the next section, the state-based FSI relies primarily on state data over
Figure 6. Example of pilot advisories during SATS HVO
which the pilot largely has control. It determines
operations.
what the pilot is doing with the aircraft, without asking him. 
The specific goal of the state-based FSI is determined by the system designers to support the application at hand. Depending on the application, the S-FSI process answers questions like, “What is the aircraft doing right now?” or “What phase of flight is the aircraft in?” or “What are the inferred intentions of the pilot?”
The SATS HVO concept is a good example of an application that benefits from S-FSI. One of the fields in the HVO extended ADS-B message is based in the pilot’s intent. Specifically, the “next waypoint type” field is expected to be “IAF” while the aircraft remains in a holding position. When the pilot intends to leave the hold and initiate the approach, the HVO software is required to begin broadcasting “MAHF” in the “next waypoint type” field. This functionality could have been implemented by adding a button the pilot presses upon begin the approach. In contrast, our software used the concept of flight segment identification to detect the pilot’s transitioning from “In Hold at 2,000’” to “On Approach Base Segment.” (Reference Fig. 5.)
 
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