Cramer-Rao Lower Bound Optimization of Flush Atmospheric Data System Sensor Placement

Abstract

Flush atmospheric data systems take measurements of the pressure distribution on the forebodies of vehicles and improve the estimate of freestream parameters during reconstruction. These systems have been present on many past entry vehicles, but design of the pressure transducer suites and the placement of the sensors on the vehicle forebody have largely relied on engineering judgment and heuristic techniques. This paper develops a flush atmospheric data system design methodology using Cramér-Rao lower bound optimization to define the smallest theoretical variance possible from the estimation process. Application of this methodology yields Pareto frontiers of possible optimal configurations and identifies the number of ports which serve as the point of diminishing returns. The methodology is tested with a simulated Mars entry, descent, and landing trajectory.

A Modified Triples Algorithm for Flush Air Data Systems That Allows a Variety of Pressure Port Configurations

“…4(e) is of particular interest as studies indicate this configuration may be optimal for FADS. 8 The initial guess on the flight angles were typically α = 20…”

“…This approach employs the potential flow model and strategic differencing of the Triples Algorithm to obtain the effective flight angles; however, the requirements on port placement are far less restrictive, allowing for configurations that are considered optimal for a FADS. 8 Once the flight angles are known, an iterative LSSE is used to capture the requisite pressures and Mach number without resorting to a potential flow model. Finally, with the Mach number known, the true flight angles are computed.…”