Sensor Array Imaging via Fresnel Field Synthesis
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Solution Overview
Problem
Conventional sensor array technologies are limited in their ability to efficiently localize scatterers in both the near-field and far-field, require multiple pulses for imaging, and are restricted to traditional beamforming and beamsteering methods, which are resource-intensive and only effective in the far-field, lacking the capability to form images with a single pulse from a stationary digital sensor array.
Innovation Solution
A system that performs temporal and spatial discrete Fourier transforms on sensor data, generates reference Fresnel fields, and uses inverse Huygens-Fresnel transfers to form images of expanded fields of view with a single pulse, enabling one-dimensional, two-dimensional, or three-dimensional imaging without the need for beamforming or beamsteering, and allowing for image formation in both near and far fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional beamforming and beamsteering methods are used for sensor array imaging, then imaging capability in the far-field is achieved, but the number of pulses required increases and time resources are excessively consumed
Solution Approach 1:
The patent employs periodic pulse transmission with a single pulse dwell approach, where the sensor array transmits one pulse and processes echoes from all directions simultaneously through Fourier transform-based imaging algorithms, eliminating the need for sequential beam steering and reducing scan time
Solution Approach 2:
The patent replaces the mechanical beamsteering system (which requires physical movement or sequential activation of beams) with a computational imaging system using Fourier transforms and point spread function synthesis, enabling parallel processing of all spatial frequencies simultaneously
2Measurement precision
If conventional beamforming methods are used for sensor array operations, then beam concentration is achieved, but power consumption increases due to multiple swept beam transmissions
Solution Approach 1:
The system uses periodic single pulse transmission instead of continuous multiple pulse sequences required for beam sweeping, where each pulse is followed by simultaneous processing of echoes from all directions, reducing the duty cycle and power consumption
Solution Approach 2:
The single pulse imaging algorithm serves multiple functions simultaneously: it performs scatterer detection, localization, and imaging for all directions in the field of view without requiring separate beamforming operations for each direction, thereby reducing overall power consumption
3Measurement precision
If Fraunhofer plane-wave beamforming is used, then beam formation is achieved, but the method is only physically possible in the far-field and cannot operate in the near-field
Solution Approach 1:
The patent changes the fundamental parameter of wavefront assumption from plane waves (far-field approximation) to spherical waves (near-field exact solution), and modifies the imaging algorithm to use Fresnel diffraction integrals and near-field point spread functions that accurately represent spherical wave propagation
Solution Approach 2:
Instead of approximating near-field spherical waves as far-field plane waves (the conventional approach), the patent inverts the approach by directly modeling spherical wave propagation using exact near-field Green's functions and Fresnel integrals, enabling accurate imaging in the near-field region
4Measurement precision
If traditional sensor array imaging methods are used, then imaging is achieved, but the field of view size is limited by the sensor array dimensions
Solution Approach 1:
The patent extends the imaging capability into the spatial frequency domain using Fourier transforms, where the field of view is determined by the sampling density in the wavenumber domain rather than the physical array dimensions, effectively decoupling FOV size from array aperture size
Solution Approach 2:
The patent introduces a point spread function (PSF) as an intermediary that characterizes the imaging system's response, allowing the field of view and resolution to be independently controlled through PSF synthesis and zero-padding techniques without changing the physical array configuration
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces the number of pulses required for imaging, increases the speed and effectiveness of sensor array operations, and enables the formation of detailed images of enlarged fields of view with a single pulse, improving the resolution and efficiency of sensor array systems.
Implementation Method 1
a sensor array which includes a plurality of sensor elements capable of transmitting waveform signals and receiving echoes
Implementation Method 2
searching for echoes from scatterers within the field of view
Implementation Method 3
performs a temporal discrete Fourier transform (DFT) on the recorded sensor element data... performs a spatial DFT on the sensor data buffer
Implementation Method 4
generates a reference Fresnel field based on the transmitted waveform, based on the size of the expanded field of view, and based on the first and second spatial reference point locations
Implementation Method 5
The processor performs Stolt mapping on the rectilinear spectrum data buffer to form nonuniformly sampled angular spectrum data
Implementation Method 6
conventionally form a 'beam' in the far-field of the sensor array to concentrate transmitted signal energy in a region of interest
Data Source
Figure 1A
Figure 1B
Figure 1C
AI summary
A system produces sensed images. The system includes a sensor array, an image display device, and a processor that generates an image illustrating contents of an expanded field of view. The processor receives sensor element data from the sensor array, performs zero padding and discrete Fourier transform to result in a sensor wavenumber data buffer. The processor determines reference point locations, and generates a reference Fresnel field. The processor obtains an inverse Huygens- Fresnel transfer data buffer based on the reference Fresnel field. The processor multiplies each data element of the sensor wavenumber buffer with each corresponding data element of the inverse Huygens-Fresnel transfer data buffer. The processor generates a rectilinear spectrum data buffer based on the multiplication. The processor performs Stolt mapping and uniformly resampling to achieve image data.