Method for performing a data acquisition task using rectification depending on a fundamental truth

Abstract

The invention relates to a method (100) for performing a data acquisition task using rectification depending on a digital twin, comprising the following steps, which are performed by a node (10) of a system (20): - Providing (101) a digital twin of a basic truth of an environment (1), wherein the basic truth is specified by at least one known static object and its respective position in the environment (1), - Performing (102) a detection task towards the environment (1) in order to detect at least one other object in the environment (1), - Performing (103) a rectification with respect to a reflection of the at least one other recognized object depending on the provided (101) basic truth. Furthermore, the invention relates to a system and a computer program.

Description

[0001] The invention relates to a method for performing a data acquisition task using rectification as a function of a fundamental truth. Furthermore, the invention relates to a computer program, a system, and a storage medium for this purpose. State of the art

[0002] Distributed Integrated Acquisition and Communication (DISAC) systems have emerged as a promising approach to leveraging existing communications infrastructure for data collection. These systems utilize specific signals transmitted through the communications network to enable distributed acquisition across a wide range of applications, including environmental monitoring, disaster management, and industrial automation. By upgrading existing communications infrastructure, DISAC systems offer a cost-effective and scalable solution for collecting environmental data or monitoring specific parameters. However, reliable signal transmission in such systems is often hampered by various distortions, including noise, interference, and decay, which can degrade the quality of the received data.To overcome these limitations, recent research has focused on incorporating basic truth information into signal equalization techniques for DISAC systems, enabling adaptive adjustment of equalization parameters based on actual channel characteristics.

[0003] Obtaining accurate baseline data for signal equalization often presents a challenge, particularly when dealing with conditions such as those found in indoor environments. Therefore, it is an object of the present invention to overcome these disadvantages and provide an improved acquisition procedure that utilizes information related to the environment. Disclosure of the invention

[0004] According to aspects of the invention, a method with the features of claim 1, a computer program with the features of claim 8, a system with the features of claim 9, and a computer-readable storage medium with the features of claim 10 are provided. Further features and details of the invention are disclosed in the respective dependent claims, the description, and the drawings. Features and details described in the context of the method also correspond to the computer program, the system, and the storage medium according to the invention, and vice versa.

[0005] According to one aspect of the invention, a method for performing a data acquisition task using rectification based on a fundamental truth is provided. The method comprises the following steps, which are performed by a node of the system, in particular a distributed integrated data acquisition and communication system (DISAC system). The steps can be performed repeatedly and / or sequentially.

[0006] In a first step, a digital twin of a basic truth of an environment is provided, whereby the basic truth is specified by at least one known static object and its respective position in the environment.

[0007] In a further step, a detection task is performed with respect to the environment in order to identify at least one other object in the environment. In a further step, a rectification is performed with respect to a reflection of the at least one identified other object, depending on the provided basic truth.

[0008] This allows the system to utilize environmental features and create a baseline using measurements or cameras. The system can be pre-calibrated to improve acquisition task performance. The digital twin of the baseline, which contains information about at least one known static object and its respective position, advantageously enables adaptive adjustment of equalization parameters based on actual channel characteristics. This results in improved signal quality and enhanced system performance, making it more reliable for environments where the acquisition system can be calibrated before the actual acquisition task. Furthermore, the system can be (pre-)calibrated by utilizing the (static) environmental features and creating a baseline using measurements or cameras to improve acquisition task performance.The digital twin of the reference data, containing information about at least one known static object and its respective position, enables adaptive adjustment of equalization parameters. This leads to improved signal quality and enhanced system performance. Furthermore, the calibration process can be streamlined by machine learning algorithms that learn from the generated reference data and adaptively adjust the parameters of the DISAC system in real time. This intelligent equalization capability allows the system to proactively compensate for changes in the environment, ensuring reliable data transmission and accurate acquisition results.

[0009] In another example, the environment can be provided as an environment specified by the presence of at least one static object that reflects detection signals, or by the presence of one or more fixed objects that reflect detection signals.

[0010] A static or fixed object can be understood as an element that is permanently attached or anchored in a specific position and cannot be easily moved. This includes structures such as buildings, statues, monuments, and other installations intended to remain in a fixed position for an extended period or indefinitely. Examples of such a fixed or static object include (among others) machinery, a wall, a sign, a plant such as a tree or bush, a machine, a box, a piece of furniture, or the like.

[0011] Equalization can be understood as a process for adjusting signal processing parameters in real time to compensate for channel interference and ensure reliable communication in distributed systems. The invention uses fundamental truth information to adaptively adjust the equalization parameters based on the actual channel characteristics, resulting in improved signal quality and enhanced system performance.

[0012] The system, in particular the distributed integrated acquisition and communication (DISAC) system, can be an advanced technological framework that combines acquisition and communication functions in a unified network. These systems can be designed to improve the efficiency, accuracy, and functionality of both data collection (acquisition) and data transmission (communication) by utilizing distributed architectures. Such a DISAC system can comprise multiple interconnected nodes distributed across various locations in the environment. Each node is capable of both acquisition and communication. These nodes, or base stations, are equipped with various sensors (e.g., temperature, pressure, motion, optical, acoustic) to collect data from their environment in real time. The DISAC system can monitor environmental conditions, detect anomalies, and collect data for analysis.

[0013] Signal equalization can be understood as a technique used in communication systems to correct distortions and reduce interference that occur during signal transmission. These distortions and interferences can arise due to numerous factors such as multipath propagation, bandwidth limitations, and noise. The goal of equalization is to restore the original signal at the receiving end as accurately as possible.

[0014] It is also possible that the procedure includes the following further steps: - Identifying a reflection, preferably several reflections, from the at least one known static object from the provided basic truth, - Performing an equalization with respect to a reflection of the at least one known static object depending on the provided basic truth.

[0015] Providing a digital twin of a baseline can enable pre-equalization of signals for improved acquisition system performance. By using environmental features, such as walls and / or stationary objects, to calibrate the system, accurate reflections from known static objects can be identified and used for equalization, resulting in improved signal quality and reliable data transmission. The digital twin serves as a reference point, allowing the process to adjust equalization parameters based on actual channel characteristics, thereby improving acquisition task results. By leveraging the static features of walls and stationary objects, the system can accurately identify reflections from known objects and adaptively adjust equalization parameters to mitigate signal distortions such as noise, interference, and decay.

[0016] It is also possible that the procedure includes the following further steps: - Establishing a basic truth about the environment by conducting a survey of at least one known static object in the environment, - Mapping the at least one known static object and its respective position onto a digital twin and storing this to provide a basic truth for performing the rectification, - Calibrating the node based on the performed equalization with respect to a reflection of the at least one known static object depending on the provided fundamental truth.

[0017] The method may provide a digital twin of a fundamental truth that specifies at least one known static object and its respective position within an environment. This fundamental truth enables rectification with respect to reflections from detected objects, thereby improving the acquisition task performance. The provided digital twin can be used to calibrate the system by performing rectification with respect to reflections from at least one known object based on the provided fundamental truth. It is possible that the system's adaptability is further enhanced by machine learning algorithms that can learn from the digital twin and adjust rectification parameters in real time to optimize acquisition performance.This intelligent adaptation allows the system to effectively handle changes in the environment, such as new static equipment, furniture, or decorations, without requiring manual recalibration.

[0018] In another example, the method according to the invention can include an additional step: using the digital twin to predict and pre-equalize signals for anticipated acquisition tasks, thereby ensuring seamless integration of new data into the system. This predictive equalization can be based on historical data patterns, environmental monitoring, or even user-defined preferences.

[0019] It is possible that the procedure includes the following further step: - Providing a list of at least one other and / or at least one known static object and its respective position for at least one other node of the DISAC system.

[0020] It is possible that the process for performing a data acquisition task using rectification, dependent on a digital twin, can be further improved by incorporating this feature. By providing a list of localized objects and their respective positions to at least one other node in the DISAC system, the nodes in the network can share this basic truth information, enabling them to pre-correct signals and improve data acquisition system performance even more effectively. This can lead to better signal quality, reduced errors, and improved overall system reliability, enabling more accurate and efficient data acquisition tasks in various environments.

[0021] It is also possible that the procedure includes the following additional steps during execution: - Sending a detection signal to the environment, - Receiving at least one reflection of the detection signal.

[0022] This has the advantage that the feature involves sending a detection signal to the environment and receiving at least one reflection of the detection signal. This allows for rectification with respect to the detected object, taking into account the provided ground truth from the digital twin. The rectification process can then utilize the known static objects and their respective positions in the environment to improve the detection task performance.

[0023] It is possible that the acquisition task is based on monostatic, bisstatic, or multistatic environmental sensing. This has the advantage that the acquisition task utilizes the monostatic, bisstatic, or multistatic sensor functionalities to achieve improved signal quality and system performance. By utilizing the provided ground truth and digital twin of the environment, the invention offers the advantage of adaptively equalizing signals based on actual channel characteristics, thereby reducing noise, interference, and decay. This enables more accurate data collection and transmission in dynamic environments.

[0024] For example, cameras equipped with specialized software can be used to create high-fidelity 3D models of the environment, enabling precise tracking of object movements and reflections. This captured information can then be used to pre-correct signals and adaptively adjust correction parameters in real time, allowing for more accurate data collection and transmission.

[0025] This also allows monostatic, bistatic or multistatic acquisition functionalities to be advantageously extended to incorporate advanced signal processing techniques such as beam focusing and spatial filtering.

[0026] It is also possible that the digital twin is located at the node, in the system, in particular in a DISAC system or a cloud system.

[0027] This enables efficient processing and storage of raw data, as well as real-time rectification and execution of the data acquisition task. The digital twin's location can be selected based on the specific requirements of the data acquisition task and the available computing resources. Furthermore, the digital twin can be strategically positioned within the system or even in a cloud-based infrastructure, facilitating efficient processing and storage of raw data. This distributed architecture enables seamless communication between nodes, allowing for real-time data exchange and synchronization.

[0028] In another aspect of the invention, a computer program, in particular a computer program product, can be provided, comprising instructions which, when executed by a computer, cause the computer to perform the method according to the invention. Therefore, the computer program according to the invention can have the same advantages as described in detail with reference to a method according to the invention.

[0029] In another aspect of the invention, a system, in particular a DISAC system, is provided, wherein the system comprises at least one node for carrying out the method according to the invention. Therefore, the system according to the invention has the same advantages as described in detail with reference to the method according to the invention.

[0030] In a further aspect of the invention, a data processing device can be provided that is designed to execute the method according to the invention. For example, a computer can be provided as such a device, which executes the computer program according to the invention. The computer can contain at least one processor that can be used to execute the computer program. Furthermore, non-volatile data storage can be provided in which the computer program can be stored and from which the computer program can be read by the processor for execution.

[0031] According to another aspect of the invention, a computer-readable storage medium can be provided that comprises the computer program according to the invention and / or instructions which, when executed by a computer, cause the computer to perform the steps of the method according to the invention. The storage medium can be a data storage device, such as a hard disk and / or non-volatile memory and / or a memory card and / or a solid-state drive. The storage medium can, for example, be integrated into the computer.

[0032] Furthermore, the method according to the invention can be implemented as a computer-implemented method. Alternatively or additionally, at least one of the disclosed method steps can be computer-implemented and / or automated.

[0033] Further advantages, properties, and details of the invention will become apparent from the following description, in which embodiments of the invention are described in detail with reference to the drawings. In this context, the features mentioned in the claims and in the description can be essential to the invention, individually or in any combination. The drawings show: Fig. 1: a method, a computer program, a storage medium and a system according to embodiments of the invention, Fig. 2: a schematic diagram of a process flow according to embodiments of the invention.

[0034] The core of the invention lies in the use of the environment, in particular the walls and immovable objects, which are often captured as a by-product of the capture task, to calibrate a system, such as a distributed integrated capture and communication system (DISAC system).

[0035] Fig. Figure 1 shows a method 100, a system 20, a node 10, a computer program 50 and a computer-readable storage medium 15 according to embodiments of the invention.

[0036] Fig. Figure 1 shows in particular an embodiment of a method 100 for performing a detection task using rectification depending on a digital twin, comprising the following steps, which are performed by a node 10 of a system 20. In step 101a, a digital twin of a basic truth of an environment is provided, wherein the basic truth is specified by at least one known static object and its respective position in the environment. In a further step 102, a detection task is performed with respect to the environment, for example, to detect targets or target objects in the environment, in particular, for example, in an indoor, outdoor, or indoor-like environment.

[0037] In step 103, a correction is performed with respect to a reflection of at least one detected object depending on the provided 101 basic truth.

[0038] A basic truth is established using the communication infrastructure, for example, a communication network, to perform data acquisition via a distributed integrated data acquisition and communication system. A key attribute of this communication infrastructure, at least in a terrestrial network, is that the position and orientation of a node or base station are known and static. This can also be the case for a subset of the objects in the acquisition environment. This subset of static or immobile objects can be used for the basic truth, which can be identified beforehand and precisely represented in a so-called digital twin.

[0039] Once the acquisition task begins, the DISAC system can receive reflections from detected objects. The DISAC system can then use the a priori known basic truth of the known static objects in the environment from the digital twin to perform rectification and improve the performance of the acquisition system.

[0040] In this context, a digital twin can be understood as a virtual copy of a physical object, such as the environment, which is used to simulate and analyze its behavior to support optimized performance. For example, the digital twin can advantageously utilize a 2D camera image of an object or the environment, which can be enriched with depth information and sensor information from the captured objects. The digital twin can support material recognition of captured objects based on electromagnetic properties stored within the twin. By using a digital twin to simulate the static objects of the environment, the invention can correct signal reflections from known objects, enabling real-time correction and acquisition task execution.

[0041] Fig. Figure 2 shows a schematic diagram of a process flow according to embodiments of the invention. Fig. Figure 2 further illustrates an environment 1, such as an indoor environment.

[0042] The in Fig. The exemplary process flow shown in Figure 2 can be executed, for example, at a node 10 or a base station 10 of a system 20. It is possible that the system 20 could, for example, comprise a distributed ISAC system (DISAC system) that executes the process at the embodiment shown in Figure 2. Fig. 2 executes.

[0043] In step 201, the baseline model of the indoor environment can be created. This can be achieved, for example, using a measurement action, such as with surveying equipment like LiDAR and / or by using cameras, which can be used in combination (later) in the DISAC task, such as a data acquisition task for indoor environment 1. During this step 201, the created baseline model can be stored in a digital twin for further use during the data acquisition task. The digital twin containing the baseline model can be used to calibrate system 20, which is initiated by node 10. Furthermore, this digital twin can be stored in a cloud system, at the node, or in a local system. This digital twin can be linked to surrounding nodes or base stations (in Fig. 2 not shown) are shared and are included in the DISAC system.

[0044] In particular, these nodes can be enabled to perform (requested) acquisition tasks in step 202 by sending signals and receiving reflections of these signals, for example, depending on an acquisition task based on monostatic, bistatic, or multistatic acquisition. Based on this shared use, the surrounding nodes of system 20 can also use the digital twin, which contains the fundamental truth, to improve their accuracy and the reliability of their measurements.

[0045] In step 203, node 10 can identify reflections from known static objects in the interior environment from the digital twin that comprises the baseline. Optionally, node 10 can perform a rectification based on the known position of the baseline static objects in the digital twin.

[0046] In step 204, node 10 can specify an equalization factor for signal equalization to calibrate system 20 depending on the digital twin that includes the basic truth.

[0047] In step 205, the node performs the same rectification on remaining (detected) objects based on the digital twin. The remaining objects can be the detected moving objects. These are rectified, which, as a result (in a further step), can provide a list of precisely located moving objects. This signal rectification technique enables an improved detection result depending on the use of the digital twin, which contains the underlying data.

[0048] In another embodiment, the steps for identifying reflections from the known static objects and for performing an equalization based on the known position a priori can be carried out during step 201 and fine-tuned during the execution of step 205.

[0049] The above explanation of the embodiments describes the present invention in the context of examples. Of course, individual features of the embodiments can be freely combined with one another, provided that this is technically appropriate and does not deviate from the scope of the present invention.

Claims

[1] Method (100) for performing a data acquisition task using rectification depending on a digital twin, comprising the following steps performed by a node (10) of a system (20): - Providing (101) a digital twin of a basic truth of an environment (1), wherein the basic truth is specified by at least one known static object and its respective position in the environment (1), - Performing (102) a detection task towards the environment (1) in order to detect at least one other object in the environment (1), - Performing (103) a rectification with respect to a reflection of the at least one other recognized object depending on the provided (101) basic truth. [2] Method (100) according to claim 1, characterized by , that the procedure (100) includes the following further steps: - Identifying a reflection from the at least one known static object from the provided basic truth, - Performing an equalization with respect to the reflection of the at least one known static object depending on the provided basic truth. [3] Method (100) according to any one of the preceding claims, characterized by , that the procedure (100) includes the following further steps: - Establishing a basic truth about the environment (1) by carrying out a survey of the at least one known static object of the environment (1), - Mapping the at least one known static object and its respective position onto a digital twin and storing this to provide a basic truth for performing the rectification, - Calibrating the node (10) based on the equalization performed with respect to a reflection of the at least one known static object depending on the provided basic truth. [4] Method (100) according to any one of the preceding claims, characterized by , that the procedure (100) includes the following further step: - Providing a list of the at least one other and / or the at least one known static object and its respective position for at least one further node of the system (20). [5] Method (100) according to any one of the preceding claims, characterized by , that the procedure (100) includes the following further steps during its execution: - Sending a detection signal to the environment (1), - Receiving at least one reflection of the detection signal. [6] Method (100) according to any one of the preceding claims, characterized by, that the detection task is based on a monostatic or bistastatic or multistatic detection towards the environment (1). [7] Method (100) according to any one of the preceding claims, characterized by that the digital twin is located at the node (10), in the system (20) or in a cloud system. [8] Computer program (50) comprising instructions which, when the computer program (50) is executed by a computer (11) of a node (10), cause the computer (10) to execute the method (100) according to any of the preceding claims. [9] System (20), in particular a distributed integrated acquisition and communication system (20) comprising at least one node (10) for performing the method (100) according to any one of claims 1 to 7. [10] Computer-readable storage medium (15) comprising instructions which, when executed by a computer (11), cause the computer (11) to perform the steps of the method (100) according to any one of claims 1 to 7.

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