A SYSTEM AND A METHOD FOR IDENTIFYING OBJECT’S REFLECTIVITY OF SYNTHETIC APERTURE RADAR (SAR) IMAGES

Abstract

ABSTRACT A SYSTEM AND A METHOD FOR IDENTIFYING OBJECT’S REFLECTIVITY OF SYNTHETIC APERTURE RADAR (SAR) IMAGES The system (200) comprises a radar signal transmitter (202), radar receiver (204), signal processing module (206), reconstruction module (208), and material identification module (210). The radar signal transmitter transmits FMCW signals at sub-THz frequency toward a target object, while the receiver captures reflected signals. The signal processing module applies a 2D FFT to extract reflectivity data from these signals. The reconstruction module combines data from multiple scans to create a reconstructed reflectivity image. The material identification module then compares this image with reference data to determine the target's material composition. This system improves identification accuracy and efficiency by leveraging synthetic aperture radar (SAR) technology for detailed material characterization, reducing screening time and enhancing safety through faster, more reliable material identification based on reflectivity.

Specification

Description:FIELD
The present disclosure is primarily related to the field of electrical and electronics engineering, more particularly the present disclosure is a system and method for the classification of objects based on their reflectivity based on the SAR technique.
DEFINITIONS
As used in the present disclosure, the following terms are generally intended to have the meaning as set forth below, except to the extent that the context in which they are used indicates otherwise.
Frequency-Modulated Continuous Waves (FMCW) - The term "FMCW" refers to a radar signal modulation technique where the transmitted signal's frequency varies continuously over time. The FMCW is used to measure the distance and velocity of objects, such as in automotive radar applications.
Two-Dimensional Fast Fourier Transform (2D FFT) -The term "2D FFT" refers to an algorithm that transforms two-dimensional signals or images from the spatial domain to the frequency domain, widely used in signal processing and image analysis.
Synthetic Aperture Radar (SAR) -The term "SAR" refers to a radar technique that creates detailed images by moving the radar antenna over a target area and using signal processing to produce high-resolution images, which is commonly used in remote sensing and surveillance.
BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
In many public areas, such as airports and bus stations, security screening is required at entry and exit points. One of the biggest challenges in ensuring the safety and security of these locations is determining the contents of bags. Traditionally, screening the contents of the bags mainly focuses on detecting the shape, size, and position of objects, which can be time-consuming and often fail to accurately identify materials, especially when different objects are made from similar substances. This leads to inefficiencies and potential security risks, as the exact nature of the contents may remain unclear, making it difficult to ensure the safety of the public in these areas.
Further, in public spaces such as airports, bus stations, and other high-security areas, traditional screening methods are employed to ensure safety by checking for prohibited or dangerous items in personal belongings. These conventional methods typically involve the use of X-ray machines, manual bag searches, and metal detectors. While effective to some extent, these methods are considered invasive because they require either physical interaction with the objects or subjecting them to radiation-based scanning processes.
Therefore, there is a need for a system to detect the object's reflectivity based on synthetic aperture radar (SAR) images and a method thereof that alleviates the aforementioned drawbacks.
OBJECTS
Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows:
It is an object of the present disclosure to ameliorate one or more problems of the prior art or to at least provide a useful alternative.
An object of the present disclosure is to provide a system for identifying the object's reflectivity.
Another object of the present disclosure is to provide a system that enhances the accuracy, resolution, and speed of detection and classification of objects while screening.
Still another object of the present disclosure is to provide a system that enhances the security screening due to the non-intrusive real-time identification of luggage contents.
Yet another object of the present disclosure is to provide a system that implements advanced radar technology.
Still another object of the present disclosure is to provide a system that uses reflectivity for the identification of objects.
Yet another object of the present disclosure is to provide a system that consumes less time for screening of the object.
Still another object of the present disclosure is to provide a method for identifying the object's reflectivity based on reconstructed image using Synthetic Aperture Radar (SAR) technique.
Yet another object of the present disclosure is to provide a non-invasive, real-time identification method that reduces manual inspections.
Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.

SUMMARY
The present disclosure envisages a system for identifying the object's reflectivity of synthetic aperture radar (SAR) images.
The system comprises a radar signal transmitter, a radar receiver, a signal processing module, a reconstruction module, and a material identification module.
The radar signal transmitter is configured to transmit FMCW signals at a sub-THz frequency toward a target object within a scanning area. The radar receiver is configured to be set up to receive radar signals reflected from the target object.
The signal processing module applies a 2D fast Fourier transform (FFT) to the reflected radar signals to extract reflectivity information and determine the reflectivity data.
The reconstruction module combines reflectivity data from multiple scanning areas to create a reconstructed reflectivity image of the target object.
Finally, a material identification module compares the reconstructed reflectivity image with reference data to determine the material composition of the target object based on its reflectivity data.
The present disclosure envisages a method for identifying the object's reflectivity of Synthetic Aperture Radar (SAR) images. The Frequency-Modulated Continuous Waves (FMCW) radar signals at a sub-THz frequency are transmitted toward a target object within a defined scanning area. The FMCW radar signals are transmitted using a synthetic aperture radar (SAR) configuration.
In an embodiment, the sub-THz frequency is in the range of approximately 120 GHz.
The reflected radar signals are received from the target object. The reflected signals are processed using a two-dimensional (2D) fast Fourier transform (FFT) to extract reflectivity information from the target object.
The reflectivity data of the target object is received based on the reflectivity information. These techniques enhance the distinction between different materials with varying reflectivity. The reflectivity data from multiple scanning areas is combined to create a reconstructed reflectivity image of the target object. These reflectivity data from multiple scanning areas involve merging data from various scan perspectives to mitigate occlusions and provide a more comprehensive view of the target object. The scanning area for the object is defined as a 100x100 unit area, and multiple scans are performed to create a comprehensive view of the object's reflectivity.
The reconstructed reflectivity image is compared with a reference model to determine the material properties of the target object based on its reflectivity data. The material properties of the target object are determined by calculating its refractive index based on the reflectivity information extracted from the radar signal, allowing for the distinction between materials with similar shapes but different refractive properties.
The chirp modulation to the FMCW radar signals is applied to vary the frequency of the radar frequency over time to improve resolution and enhance the ability to detect material properties based on reflectivity.
The real-time processing of the reflected radar signals is performed and reflectivity data, enabling immediate feedback on the material properties of the target object for rapid decision-making in high-traffic security environments.
The method for identifying the object's reflectivity of Synthetic Aperture Radar (SAR) images includes the following steps:
• transmitting FMCW radar signals at a sub-THz frequency toward a target object within a defined scanning area;
• receiving reflected radar signals from the target object;
• processing the reflected signals using a two-dimensional (2D) fast Fourier transform (FFT) to extract reflectivity information from the target object;
• determining the reflectivity data of the target object based on the reflectivity information;
• combining reflectivity data from multiple scanning areas to create a reconstructed reflectivity image of the target object; and
• comparing the reconstructed reflectivity image with a reference model to determine the material properties of the target object based on its reflectivity data.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING
A system and method for identifying the object's reflectivity of synthetic aperture radar (SAR) images of the present disclosure will now be described with the help of the accompanying drawings, which:
Figure 1 illustrates a method for identifying the object's reflectivity of synthetic aperture radar (SAR) images, by the present disclosure;
Figure 2 illustrates a block diagram of the system for identifying the object's reflectivity of synthetic aperture radar (SAR) images, following the present disclosure;
Figure 3 illustrates a comparison between the true image and the reconstructed image based on reflectivity, by the present disclosure;
LIST OF REFERENCE NUMERALS
100 - Method
200 - System
202 - Radar signal transmitter
204- Radar receiver
206 - Signal processing module
208 - Reconstruction module
210 - Identification module
DETAILED DESCRIPTION
Embodiments, of the present disclosure, will now be described with reference to the accompanying drawings.
Embodiments are provided so as to thoroughly and fully convey the scope of the present disclosure to the person skilled in the art. Numerous details are set forth, relating to specific components, and methods, to provide a complete understanding of embodiments of the present disclosure. It will be apparent to the person skilled in the art that the details provided in the embodiments should not be construed to limit the scope of the present disclosure. In some embodiments, well-known processes, well-known apparatus structures, and well-known techniques are not described in detail.
The terminology used, in the present disclosure, is only for the purpose of explaining a particular embodiment and such terminology shall not be considered to limit the scope of the present disclosure. As used in the present disclosure, the forms "a," "an," and "the" may be intended to include the plural forms as well, unless the context suggests otherwise. The terms "including," and "having," are open-ended transitional phrases and therefore specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not forbid the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The particular order of steps disclosed in the method and process of the present disclosure is not to be construed as necessarily requiring their performance as described or illustrated. It is also to be understood that additional or alternative steps may be employed.
When an element is referred to as being "engaged to," "connected to," or "coupled to" another element, it may be directly engaged, connected, or coupled to the other element. As used herein, the term "and/or" includes any combinations of one or more of the associated listed elements.
In most public places, entry, and exit points to and from airports and bus stations require security screening. Telling what is inside the bag is one of the most challenging encounters for the safety and security of the people in such areas. Traditional screening technologies focus on detecting the shape, size, and position of objects, which can be time-consuming and often fail to accurately identify materials, especially when different objects are made from similar substances.
Further, in public spaces such as airports, bus stations, and other high-security areas, traditional screening methods are employed to ensure safety by checking for prohibited or dangerous items in personal belongings. These conventional methods typically involve the use of X-ray machines, manual bag searches, and metal detectors. While effective to some extent, these methods are considered invasive because they require either physical interaction with the objects or subjecting them to radiation-based scanning processes.
To address the aforementioned problems, the present disclosure envisages a system (hereinafter referred to as a "system 200") and method for identifying the object's reflectivity of synthetic aperture radar (SAR) images. The method 100 and system 200 are now described in Figure 1 and Figure 2 respectively.
Figure 1 illustrates the method 100 for identifying the object's reflectivity of synthetic aperture radar (SAR) images, by an embodiment of the present disclosure. The order in which method 100 is described is not intended to be construed as a limitation, and any number of the described method steps may be combined in any order to implement method 100, or an alternative method. Furthermore, method 100 may be implemented by processing resource or computing device(s) through any suitable hardware, non-transitory machine-readable medium/instructions, or a combination thereof.
The method 100 comprises the following steps:
At step 102, method 100 includes transmitting FMCW radar signals at a sub-THz frequency toward a target object within a defined scanning area, wherein the sub-THz frequency is in the range of approximately 120 GHz.
At step 104, method 100 includes receiving reflected radar signals from the target object.
At step 106, method 100 includes processing the reflected signals using a two-dimensional (2D) fast Fourier transform (FFT) to extract reflectivity information from the target object.
At step 108, method 100 includes determining the reflectivity data of the target object based on the reflectivity information, wherein the reflectivity data is normalized to improve image contrast and resolution using a set of normalization techniques.
In an embodiment, these techniques enhance the distinction between different materials with varying reflectivity. The reflectivity data from multiple scanning areas may be combined to create a reconstructed reflectivity image of the target object. These reflectivity data from multiple scanning areas involve merging data from various scan perspectives to mitigate occlusions and provide a more comprehensive view of the target object. The scanning area for the object is defined as a 100x100 unit area, and multiple scans are performed to create a comprehensive view of the object's reflectivity.
Further comprises performing real-time processing of the reflected radar signals and reflectivity data, enabling immediate feedback on the material properties of the target object for rapid decision-making in high-traffic security environments.
At step 110, method 100 includes combining reflectivity data from multiple scanning areas to create a reconstructed reflectivity image of the target object, wherein the step of combining reflectivity data from multiple scanning areas, comprises combining data from multiple scan perspectives to mitigate occlusions and providing a more comprehensive view of the target object.
In step 112, method 100 includes comparing the reconstructed reflectivity image with a reference model to determine the material properties of the target object based on its reflectivity data.
In an embodiment the material properties of the target object may be determined by calculating its refractive index based on the reflectivity information extracted from the radar signal, allowing for the distinction between materials with similar shapes but different refractive properties. The chirp modulation to the FMCW radar signals is applied to vary the frequency of the radar frequency over time to improve resolution and enhance the ability to detect material properties based on reflectivity.
Therefore, by using sub-THz frequencies (around 120 GHz) and FMCW radar signals the reflectivity data offers significant benefits. The high-frequency radar signals provide finer detail of, improving image resolution and contrast which is crucial for security and material inspection. The normalized reflectivity data used for material distinction, detecting subtle differences between materials with similar shapes but different reflective properties. Combining data from multiple perspectives reduces occlusions and provides a comprehensive and accurate representation of the target object. The real-time processing offers immediate feedback, facilitates rapid decision-making,
The method in the present disclosure is highly suitable for high-traffic environments like airports or border control. Overall, it delivers higher resolution, material specificity, broader coverage, and real-time processing, making it effective for security and material analysis.
Referring to Figure 2, a system (200) comprises a radar signal transmitter (202), a radar receiver (204), a signal processing module(206), a reconstruction module(208), and a material identification module(210).
The radar signal transmitter (202) is configured to transmit FMCW signals at a sub-THz frequency toward a target object within a scanning area, wherein the sub-THz frequency is in the range of approximately 120 GHz.
The radar receiver (204) is configured to receive radar signals reflected from the target object and processes to the signal processing module (206).
The signal processing module (206) is configured to apply a 2D fast Fourier transform (FFT) to the reflected radar signals to extract reflectivity information to determine the reflectivity data.
The reconstruction module (208) is configured to combine reflectivity data from multiple scanning areas to create a reconstructed reflectivity image of the target object.
The material identification module (210) is configured to compare the reconstructed reflectivity image with reference data to determine the material composition of the target object based on its reflectivity data.
Figure 3 presents a comparison between the true image and the reconstructed image based on reflectivity. The true image shows distinct, uniform vertical bars in various colors, each representing different reflectivity. These bars are clearly defined and free from noise, making it easy to distinguish between different materials.
In contrast, the reconstructed image, which uses sub-THz FMCW radar technology, shows the same vertical bars but with significant noise and color variations within each bar. This noise makes it challenging to accurately identify the reflectivities of the materials. The red markings, intended to highlight areas of different reflectivities, are not distinctly visible due to the noise and variations.
This comparison illustrates the challenges faced in imaging technology, where the accuracy and clarity of the reconstructed image are crucial for precise material identification. Despite the advanced technology, issues like noise and environmental sensitivity can impact the effectiveness of the imaging process.
The system (200) comprises a radar signal transmitter (202), radar receiver (204), signal processing module (206), reconstruction module (208), and material identification module (210). The radar signal transmitter transmits FMCW signals at sub-THz frequency toward a target object, while the receiver captures reflected signals. The signal processing module applies a 2D FFT to extract reflectivity data from these signals. The reconstruction module combines data from multiple scans to create a reconstructed reflectivity image. The material identification module then compares this image with reference data to determine the target's material composition. This system improves identification accuracy and efficiency by leveraging synthetic aperture radar (SAR) technology for detailed material characterization, reducing screening time and enhancing safety through faster, more reliable material identification based on reflectivity.
The foregoing description of the embodiments has been provided for purposes of illustration and is not intended to limit the scope of the present disclosure. Individual components of a particular embodiment are generally not limited to that particular embodiment, but, are interchangeable. Such variations are not to be regarded as a departure from the present disclosure, and all such modifications are considered to be within the scope of the present disclosure.
TECHNICAL ADVANCEMENTS
The present disclosure described herein above has several technical advantages including, but not limited to, the realization of a system to detect the object's reflectivity that:
• Improves accuracy and efficiency;
• use reflectivity for identification;
• synthetic aperture radar (SAR) imaging technology provides detailed characterization of materials, improving the reliability of the identification process;
• Decreases time of screening; and
• Enhances safety.
The aspect herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The foregoing description of the specific embodiments so fully reveals the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
The use of the expression "at least" or "at least one" suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results.
Any discussion of devices, articles, or the like that has been included in this specification is solely to provide a context for the disclosure. It is not to be taken as an admission that any or all of these matters form a part of the prior art base or were common general knowledge in the field relevant to the disclosure as it existed anywhere before the priority date of this application.
While considerable emphasis has been placed herein on the components and parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation. , Claims:WE CLAIM:
1. A method for determining the reflectivity of objects using sub-terahertz (sub-THz) frequency-modulated continuous-wave (FMCW) radar, comprising:
• transmitting FMCW radar signals at a sub-THz frequency toward a target object within a defined scanning area;
• receiving reflected radar signals from the target object;
• processing the reflected signals using a two-dimensional (2D) fast Fourier transform (FFT) to extract reflectivity information from the target object;
• determining the reflectivity data of the target object based on the reflectivity information;
• combining reflectivity data from multiple scanning areas to create a reconstructed reflectivity image of the target object; and
• comparing the reconstructed reflectivity image with a reference model to determine the material properties of the target object based on its reflectivity data.
2. The method as claimed in claim 1, wherein the sub-THz frequency is in the range of approximately 120 GHz.
3. The method as claimed in claim 1, wherein the step of determining the reflectivity data of the target object based on the reflectivity information, comprises:
• normalizing the reflectivity data to improve image contrast and resolution using a set of normalization techniques, wherein the set of normalization techniques are applied to enhance the distinction between different materials with varying reflectivity.
4. The method as claimed in claim 1, wherein the step of transmitting FMCW radar signals comprises transmitting FMCW radar signals in a synthetic aperture radar (SAR) configuration.
5. The method as claimed in claim 1, wherein the step of combining reflectivity data from multiple scanning areas, comprises combining data from multiple scan perspectives to mitigate occlusions and provide a more comprehensive view of the target object.
6. The method as claimed in claim 1, wherein the material properties of the target object are determined by calculating its refractive index based on the reflectivity information extracted from the radar signal, enables to distinction between materials with similar shapes but different refractive properties.
7. The method as claimed in claim 1, further comprises applying chirp modulation to the FMCW radar signals to vary the frequency of the radar frequency over time to improve resolution and enhance the ability to detect material properties based on reflectivity.
8. The method as claimed in claim 1, further comprises performing real-time processing of the reflected radar signals and reflectivity data, enabling immediate feedback on the material properties of the target object for rapid decision-making in high-traffic security environments.
9. The method as claimed in claim 1, wherein the scanning area for the object is defined as a 100x100 unit area, and multiple scans are performed to create a comprehensive view of the object's reflectivity.
10. A system (200) for determining the reflectivity of objects using sub-terahertz (sub-THz) frequency-modulated continuous-wave (FMCW) radar, said system (100) comprising:
• a radar signal transmitter (202) configured to transmit FMCW signals at a sub-THz frequency toward a target object within a scanning area;
• a radar receiver (204) configured to receive radar signals reflected from the target object;
• a signal processing module (206) configured to apply a 2D fast Fourier transform (FFT) to the reflected radar signals to extract reflectivity information to determine the reflectivity data ;
• a reconstruction module (208) configured to combine reflectivity data from multiple scanning areas to create a reconstructed reflectivity image of the target object; and
• a material identification module (210) configured to compare the reconstructed reflectivity image with reference data to determine the material composition of the target object based on its reflectivity data.

Dated this 28th day of October, 2024

_______________________________
MOHAN RAJKUMAR DEWAN, IN/PA - 25
OF R. K. DEWAN & CO.
AUTHORIZED AGENT OF APPLICANT
TO,
THE CONTROLLER OF PATENTS
THE PATENT OFFICE, CHENNAI

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