Compressed Scan Systems Using Torus and Lissajous Paths
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Solution Overview
Problem
Conventional scan systems, such as SEM and AFM, operate at slow speeds due to limited sensing bandwidth, leading to long scan times and difficulties in capturing dynamically changing targets.
Innovation Solution
Implementing a method where the scan sensor moves along multiple paths at faster speeds than traditional systems, using data processing to recover clear signals through compressed sampling and spatial frequency transformations, such as Torus, Ping-Pong, Lissajous, and Daisy scan paths, to achieve wider bandwidth and efficient target imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the scan sensor moves faster to reduce scan time, then productivity is improved, but measurement precision deteriorates due to limited sensing bandwidth
Solution Approach 1:
The patent applies preliminary action by designing specific scan paths (Torus, Ping-Pong, Lissajous, Daisy) that pre-structure the motion trajectory to encode spatial frequency information in a way that enables later recovery. The scan paths are carefully planned in advance to ensure that even at high speeds, the collected data contains sufficient information for accurate target reconstruction through compressed sampling algorithms.
Solution Approach 2:
The patent replaces the traditional mechanical limitation approach (slowing down the scan sensor to match bandwidth limits) with a data processing substitution. Instead of relying on the scan sensor bandwidth to naturally filter and preserve signal quality, the system uses compressed sampling theory and spatial frequency transformations to recover clear images from high-speed scan data, substituting mechanical constraints with computational methods.
2Loss of time
If the scan sensor moves faster, then loss of time is reduced, but loss of information increases due to aliasing and signal degradation
Solution Approach 1:
The patent applies dynamics by making the scan path flexible and adaptive rather than using simple linear or raster patterns. The specialized scan paths (Torus, Ping-Pong, Lissajous, Daisy) create dynamic sampling patterns that optimize information capture at high speeds. These dynamic paths ensure that spatial frequency components are distributed in a recoverable manner, preventing information loss even when the scan sensor operates beyond traditional bandwidth limits.
Solution Approach 2:
The patent changes the scanning parameters by using non-traditional scan paths that transform how spatial information is sampled. By changing from conventional scan patterns to these specialized paths, the system alters the frequency domain characteristics of the collected data, enabling compressed sampling algorithms to effectively reconstruct the target without losing critical information, thus maintaining signal integrity at higher scan speeds.
3Measurement precision
If conventional scan methods are used to maintain image quality, then measurement precision is preserved, but productivity decreases due to long scan times
Solution Approach 1:
The patent applies segmentation by dividing the scanning process into multiple passes along different segments of the scan path. Each pass collects specific spatial frequency information, and the combination of all passes reconstructs the complete target image. This segmented approach allows the scan sensor to move faster in each individual pass while the cumulative data from multiple passes maintains or even improves image quality through the compressed sampling reconstruction process.
Solution Approach 2:
The patent transitions from conventional two-dimensional raster scanning to scan paths that incorporate temporal and spatial frequency dimensions. By using scan paths like Torus and Lissajous that traverse the target in complex multi-dimensional patterns, the system captures information in a transformed domain that enables more efficient reconstruction. This dimensional transformation allows faster scanning while preserving image quality through advanced signal processing.
Data Source
AI summary
A method for building a fast scan system is provided in which a scanner moves the scan sensors faster than scanners of the prior art, even though the total distance that the scan sensors move longer. The scan system includes (a) a scan sensor that measures the scan target by moving around it, and (b) a data processing system that calculates a parameter of the scan target from the collected data. The scan sensor, which has a limited sensing bandwidth, is moved along multiple paths along the target at a scan speed that is faster than the scan speed determined by the scan sensor bandwidth, so as to obtain a clear signal directly from the scan sensor output. The target is then recovered from the scan output using a compressed sampling data recovery data processing method.