Abstract: Optical measurement of a sample that includes a structure-of-interest (SOI) optically coupled to a section having an unknown structure is optically measured using an influence map of the deviation contribution from the unknown structure. The influence map is generated by obtaining metrology data for a plurality of locations that include the SOI and unknown structure and determining the deviation contribution at each location by decoupling the deviation contribution from base contributions from the SOI and unknown structure. During measurement of a location, the deviation contribution associated with that location may be obtained from the influence map and removed from the measured data. The processed data may be fit with a model that includes a rigorous model for the SOI and an effective model for the base contribution of the unknown structure to determine one or more parameters of the SOI.

Abstract: Contamination of metrology data by non-target signals caused by the measurement spot being incident on target and non-target areas may be reduced or eliminated using local gradient based mixed modeling or a machine learning model. The local gradient based mixed modeling approach uses a mixed model based on a model of the target region and a term of the local gradient of measured signals, which may be determined from scan data. The machine learning approach obtains mixed metrology data from a plurality of locations with respect to the target. The mixed metrology data is a mixture of target signals from the target and non-target signals from a non-target area and is used by a trained machine learning model to determine target metrology data that includes target signals from the target without the non-target signals and is used to determine parameters of interest for the target.

Abstract: Systems and methods provide reception of a call to a first function, determination of a first configuration file associated with the first function, the first configuration file indicating a primary function, a secondary function and a relationship between a first property of the primary function and a second property of the secondary function, calling of the primary function and reception of a corresponding first result set, calling of the secondary function, the call to the secondary function including a filter on the second property based on values of the first result set associated with the first property, reception of a second result set corresponding to the call to the secondary function, generation of a composed result set based on the first result set, the second result set, and the relationship, and return of the composed result set in response to the call to the first function.

Abstract: Systems and methods provide reception of a call to a first function, determination of a first configuration file associated with the first function, the first configuration file indicating a primary function, a secondary function and a relationship between a first property of the primary function and a second property of the secondary function, calling of the primary function and reception of a corresponding first result set, calling of the secondary function, the call to the secondary function including a filter on the second property based on values of the first result set associated with the first property, reception of a second result set corresponding to the call to the secondary function, generation of a composed result set based on the first result set, the second result set, and the relationship, and return of the composed result set in response to the call to the first function.

Abstract: A global positioning system and dead reckoning (GPS&DR) integrated navigation system includes a GPS receiver coupled to a moving object for periodically generating GPS navigation information of said moving object, a DR system coupled to said moving object for periodically calculating DR navigation information of said moving object, and a filter coupled to said GPS receiver and said DR system for periodically calculating navigation information of said moving object, wherein said filter gets observation information by integrating said GPS navigation information and said DR navigation information according to a weight value of said GPS navigation information and a weight value of said DR navigation information, and calculates a current navigation information by integrating said observation information with previous navigation information from a plurality of previous cycles.

Abstract: A global positioning system and dead reckoning (GPS&DR) integrated navigation system includes a GPS receiver coupled to a moving object for periodically generating GPS navigation information of said moving object, a DR system coupled to said moving object for periodically calculating DR navigation information of said moving object, and a filter coupled to said GPS receiver and said DR system for periodically calculating navigation information of said moving object, wherein said filter gets observation information by integrating said GPS navigation information and said DR navigation information according to a weight value of said GPS navigation information and a weight value of said DR navigation information, and calculates a current navigation information by integrating said observation information with previous navigation information from a plurality of previous cycles.