Apparatus and method for simulating moving object in radio frequency channel
Through the equipment and methods of simulating mobile objects in the RF channel, and using components such as receiving terminals and adjustable delay circuits to generate realistic radar echoes, the problem of inaccurate target simulation in radar system tests in the prior art is solved, and the simulation capability of the radar system is improved.
Patent Information
- Application Number
- CN202411573100.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2024-01-31
- Filing Date
- 2024-11-06
- Publication Date
- 2025-08-01
AI Technical Summary
Existing RF channel simulators cannot generate mobile objects with Doppler and microDoppler effects, resulting in the target simulation in radar system testing that is not realistic enough.
Through the reception terminal, adjustable delay circuit, adjustable attenuation circuit, adjustable frequency shift circuit and antenna array, combined with processor circuits and memory circuits, the distance, cross-sectional area, speed and Doppler shift of moving objects are simulated to generate realistic radar echoes.
Realistic target simulation of radar system is achieved, unique Doppler and microDoppler signatures of various targets are simulated, and the development and testing efficiency of radar system is improved.
Smart Images
Figure CN120405586A_ABST
Abstract
Description
Technical Field
[0001] The present invention generally relates to radio detection and ranging (RADAR) echo generation, and more particularly to devices and methods for simulating moving objects in an RF channel. Background Art
[0002] Radar systems must be tested to ensure proper sensor functionality. Target simulation is an important part of verifying the overall functionality of a radar system and requires the generation of virtual radar echoes of potentially moving objects by applying time delays, Doppler frequency shifts, and attenuation in real-time and reproducibly. Nevertheless, today's RF channel simulators only generate point targets. Summary of the Invention
[0003] The aim is to overcome the above and other drawbacks.
[0004] The above and other aims are achieved by the present application. Further implementations are apparent from the description and the drawings.
[0005] A first aspect of the present invention relates to a device for simulating a moving object in a radio frequency (RF) channel. The device includes: a receiving terminal for receiving an RF signal; an adjustable delay circuit for delaying the RF signal according to a distance indication associated with the moving object; an adjustable attenuation circuit for attenuating the RF signal according to a cross-sectional area indication associated with the moving object; a processor circuit for determining a Doppler frequency shift according to a speed indication associated with the moving object and a plurality of micro-Doppler frequency shifts associated with the moving object; an adjustable frequency shift circuit for frequency-shifting the RF signal according to the Doppler frequency shift associated with the moving object; and an antenna array for transmitting the RF signal through the RF channel according to an azimuth indication and an elevation indication associated with the moving object.
[0006] The device may further include a memory circuit configured to store one or more of the following object parameters: the distance indication associated with the moving object, the cross-sectional area indication associated with the moving object, the speed indication associated with the moving object, the azimuth indication associated with the moving object, and the elevation indication associated with the moving object.
[0007] The processor circuit may also be arranged to retrieve the plurality of micro-Doppler frequency shifts from a record.
[0008] The memory circuit may further include the record.
[0009] The processor circuit may also be arranged to retrieve the plurality of micro-Doppler frequency shifts in accordance with a motion description.
[0010] The processor circuit may also be arranged to provide the motion description in accordance with a signature description of the moving object and / or an orientation of the moving object.
[0011] The memory circuit may also be configured to store one or more of the following object parameters: the signature description of the moving object, and the orientation of the moving object.
[0012] The processor circuit may also include a generative artificial intelligence (AI) model for providing a corresponding motion description.
[0013] The RF channel may form part of a plurality of multipath RF channels that differ in one or more object parameters; and the processor circuit may also be arranged to simulate the moving object in each of the plurality of multipath RF channels.
[0014] The moving object may form part of a plurality of moving objects that differ in one or more object parameters; and the processor circuit may also be arranged to simulate each of the plurality of moving objects in a respective one of the plurality of multipath RF channels.
[0015] The plurality of micro-Doppler frequency shifts of the respective multipath RF channels may depend on one or more of their object parameters.
[0016] The RF signal may include one of a RADAR signal and a fifth-generation (5G) 3GPP RF signal.
[0017] A second aspect of the present invention relates to a method for simulating a moving object in a radio frequency (RF) channel. The method includes: receiving an RF signal; delaying the RF signal in accordance with a distance indication associated with the moving object; attenuating the RF signal in accordance with a cross-sectional area indication associated with the moving object; determining a Doppler frequency shift in accordance with a speed indication associated with the moving object and a plurality of micro-Doppler frequency shifts associated with the moving object; frequency-shifting the RF signal in accordance with the Doppler frequency shift associated with the moving object; and transmitting the RF signal through the RF channel in accordance with an azimuth indication and an elevation indication associated with the moving object.
[0018] A third aspect of the present invention relates to a system, including: an apparatus for simulating a moving object in a radio frequency (RF) channel according to the first aspect; and a sensor circuit for classifying the moving object in accordance with an RF signal received from the apparatus.
[0019] Beneficial effects
[0020] In the field of radar technology, the ability to accurately simulate radar targets is crucial for the development and testing of radar systems. This is where the proposed channel / fading simulator with micro-Doppler effect comes into play.
[0021] In the real world, radar systems encounter various targets, each with its unique motion and structural characteristics. These characteristics affect the radar signals reflected back to the radar receiver, creating unique Doppler and micro-Doppler signatures for each target. For example, rotating helicopter blades or moving human limbs each generate distinct micro-Doppler signatures.
[0022] The proposed technology can simulate these unique signatures, thus mimicking radar targets in a realistic manner. By considering the environment / object signatures and converting them into motion types, the simulator can generate the micro-Doppler effects associated with various targets. This includes the swinging of an arm, the rotation of a turbine, or the vibration of a vehicle, etc.
[0023] In addition, the simulator can modify the Doppler frequency added to the signal to vary it over time, thus reflecting the dynamic nature of real-world targets. Based on parameters such as distance, resolution, and angle, the simulator can add micro-Doppler frequency components to one or more channels. This allows for the simulation of complex scenarios where a radar system may encounter multiple targets with different characteristics.
[0024] In addition, the technology can simulate the impact of micro-Doppler on other parameters. For example, the micro-Doppler effect can change the radar cross-section (RCS), distance, or angle of a target, thereby affecting the received radar signal. This further enhances the realism of radar target simulation.
[0025] That is to say, the present invention applies micro-Doppler signatures to artificially generated objects in an RF channel simulator. To this end, the characteristics of special object types (e.g., the arm movement of a pedestrian, the vibration of a vehicle, the rotation of a turbine) are mapped onto one or more RF channels. In this way, points distributed in space with different motion patterns can be mapped and superimposed onto one or more moving objects of an RF channel simulator with given characteristics (e.g., distance, angle, speed, backscattering properties).
[0026] In summary, the technology significantly improves the ability to simulate radar targets by accurately mimicking the unique Doppler and micro-Doppler signatures of various targets. This can greatly contribute to the development and testing of radar systems as it allows for the realization of realistic and comprehensive simulation scenarios.
[0027] The technical effects and advantages described herein apply equally to the devices of the first aspect and the methods of the second aspect having the corresponding features. BRIEF DESCRIPTION OF THE DRAWINGS
[0028] The above aspects and implementations will now be explained with reference to the drawings, in which like or similar reference numerals denote like or similar elements.
[0029] Unless otherwise specifically stated, the features of these aspects and implementations may be combined with each other.
[0030] The drawings should be regarded as schematic representations, and the elements shown in the drawings are not necessarily shown to scale. Instead, the individual elements are shown such that their function and general purpose are clear to those skilled in the art.
[0031] Figure 1 A system according to the present invention is shown;
[0032] Figure 2 A method according to the present invention is shown; and
[0033] Figure 3 A pedestrian micro-Doppler signature model measurement is shown. DETAILED DESCRIPTION
[0034] Figure 1 Systems 1, 3 according to the present invention are shown.
[0035] Systems 1, 3 according to the third aspect of the present invention include a device 1 according to the first aspect and a sensor circuit 3.
[0036] The device 1 is arranged to simulate a moving object in an RF channel.
[0037] The device 1 operates by considering the environment and object signatures, which are essentially unique characteristics or patterns associated with different objects or environments. These signatures can include aspects such as the shape, size, material, and motion of the object, as well as the characteristics of the environment in which the object is located.
[0038] As used herein, the moving object used herein may refer to various types of radar targets, such as a person, a bicycle, a car, a helicopter, a drone, etc.
[0039] As used herein, the RF channel may refer to a part of the gigahertz (GHz) frequency range.
[0040] The sensor circuit 3 is arranged to classify the moving object based on the RF signal 31 received from the device 1. The sensor circuit 3 may include, for example, an object detection / classification sensor for radar point clouds.
[0041] Device 1 includes a receiving terminal 11 for receiving an RF signal 121, S(jω).
[0042] The RF signal 121, S(jω) may include one of a RADAR signal and a fifth-generation (5G) 3GPP RF signal.
[0043] As used herein, radio detection and ranging or RADAR for short may refer to radio-based technologies that are used to detect targets and their attributes, such as relative distance (ranging) and relative speed with respect to an observer, and relative pivot (azimuth, elevation) with respect to a main direction.
[0044] Depending on the specific requirements of the scenario, device 1 may obtain the RF signal 121, S(jω) through the following various methods:
[0045] Direct signal acquisition: In this method, device 1 directly obtains the RF signal 121, S(jω) from a source. For example, in a 5G network, the signal may be obtained from a 5G base station. In the case of a radar signal, the signal may be directly captured from a radar transmitter.
[0046] Signal generation: Device 1 may also generate the RF signal 121, S(jω) internally. This may be achieved using a signal generator that can generate signals of various frequencies, amplitudes, and phases. Then, the generated RF signal 121, S(jω) may be modulated to mimic the characteristics of a 5G or radar signal.
[0047] Signal recording and playback: In this method, the RF signal 121, S(jω) is recorded in a real-world scenario and then played back during simulation. This allows the system to accurately replicate the conditions of the original scenario.
[0048] Signal download: Device 1 may also download the RF signal 121, S(jω) from a database or a cloud-based platform. This is particularly useful when the signal corresponds to a specific scenario or target that has been previously recorded.
[0049] Extracting a signal from a mixed signal: In some cases, the RF signal 121, S(jω) may be part of a mixed signal that contains multiple signals. The system may use signal processing techniques to extract the RF signal 121, S(jω) from the mixed signal.
[0050] Wireless signal reception: The system may wirelessly receive the RF signal 121, S(jω) using an antenna. This method is particularly useful for capturing real-world signals in a natural environment.
[0051] Wired signal reception: The initial signal can also be obtained through a wired connection. This can be achieved by connecting the system to a signal source (such as a base station or a radar transmitter) using a coaxial cable or other types of signal transmission lines. This method ensures a stable and high-quality signal input to the channel simulator.
[0052] Device 1 further includes an adjustable delay circuit 12 for delaying the RF signal 121,S(jω) according to the distance indication 122,R associated with the moving object; an adjustable attenuation circuit 13 for attenuating the RF signal 131,e -jωΔτ ·S(jω); a processor circuit 14 for determining the Doppler shift 152,Δω according to the speed indication 141,v associated with the moving object and the multiple micro-Doppler frequency shifts 142,Δω i associated with the moving object (each micro-Doppler frequency shift is distinguished by a natural number i).
[0053] It should be noted that according to a specific simulation scenario, the distance indication 122,R associated with the moving object can take different values. In a reflection scenario, where the transmission and reception of the RF signal 121,S(jω) are considered to occur at or near the location of the sensor circuit 3, the distance indication 122,R of the moving object may be related to the simulated line-of-sight distance between the moving object and the sensor circuit 3. In an obstacle scenario, where the transmission and reception of the RF signal 121,S(jω) are considered to occur at different locations of a transmitter (e.g., a 5G base station) and a receiver (i.e., the sensor circuit 3), and a moving object (e.g., an unmanned aerial vehicle (UAV), such as a drone) may partially obstruct the line of sight between the locations, the distance indication 122,R associated with the moving object may be related to the simulated signal path from the transmitter, partially reflected from the moving object, to the receiver.
[0054] As used herein, the Doppler shift may refer to the frequency modulation of the returned (coherent) radar signal due to the velocity of the target, which is caused by the carrier frequency shift of the signal known as the Doppler effect.
[0055] As used herein, the micro-Doppler shift may refer to the additional frequency modulation of the returned radar signal, which, due to the vibration, rotation, or general internal movement of the structure of the target or the structure on the target, generates sidebands about the Doppler frequency of the target. Multiple micro-Doppler frequency shifts may be referred to as a micro-Doppler signature and may indicate the type of the target or the moving object.
[0056] The process of incorporating the micro-Doppler effect into the RF signal 121, S(jω) involves modifying the Doppler frequency based on the motion characteristics of the object. This is because the Doppler shift is a function not only of the relative velocity between the source and the observer but also of the inherent motion of the object itself.
[0057] For example, Figure 3 shows a pedestrian micro-Doppler signature model measurement. The solid black line represents the ideal signature of an approximate model of the pedestrian signature. For comparison, the measured data represents the Doppler and micro-Doppler generated by the radar.
[0058] For example, in the case of a rotating or vibrating object, the Doppler frequency changes over time due to the periodic motion of the object. This change in the Doppler frequency over time is what gives rise to the micro-Doppler effect.
[0059] To achieve this in a signal processing system, the first step is to obtain a model of the object's motion. This can be a mathematical model derived from physical principles or alternatively a data-driven model obtained from measurements or simulations.
[0060] Once the motion model is obtained, it can be used to calculate the time-varying Doppler shift. This involves calculating the relative velocity between the source and the observer at each time point, taking into account the overall motion of the object (e.g., its translation or rotation) and its inherent motion (e.g., the rotation or vibration of its components).
[0061] Then, the calculated Doppler shift can be used to modulate the signal. This can be achieved using various signal processing techniques such as frequency modulation, phase modulation, or complex baseband modulation.
[0062] The hardware required for this process can include a signal generator for generating the initial signal, a signal processor for calculating the Doppler shift and modulating the signal, and a signal analyzer for verifying the results. Depending on the specific requirements of the task, the signal processor can be a digital signal processor (DSP), a field-programmable gate array (FPGA), or a general-purpose processor (GPP). The signal generator and analyzer can be stand-alone instruments or they can also be integrated into a software-defined radio (SDR) platform.
[0063] In a system designed to process and generate micro-Doppler signatures, both analog signal processing components and digital signal processing components can be used.
[0064] The micro-Doppler effect does affect other parameters such as the radar cross-section (RCS), range, and angle of the target. The methods are as follows:
[0065] Radar Cross Section (RCS): The cross-sectional area of a moving object (i.e., the target) indicates 132. RCS is a measure of the detectability of an object by radar. A larger RCS means the object is easier to detect. The micro-Doppler effect affects the RCS because it is caused by the relative motion of different parts of the target. For example, the rotation of helicopter blades or the vibration of a car engine causes fluctuations in the RCS over time. This can make the target more or less detectable depending on the specific characteristics of the motion.
[0066] Range: The range of a moving object (i.e., the target) indicates 122. R is the distance from the radar to the target. The micro-Doppler effect affects range measurement because it causes changes in the Doppler shift used to measure the range. For example, if the target is rotating, the part of the target moving towards the radar will cause a positive Doppler shift, while the part moving away from the radar will cause a negative Doppler shift. This can cause an expansion of the measured Doppler frequency, resulting in an error in the range measurement.
[0067] Angle: The azimuth angle indication 162, φ and the elevation angle indication 163, θ of a moving object (i.e., the target) represent the direction of the target relative to the radar. The micro-Doppler effect affects angle measurement because it causes phase changes in the received signal used to measure the angle. For example, if the target is rotating, the phase of the signal reflected from the target will change over time. This can cause an expansion of the measured phase, resulting in an error in the angle measurement.
[0068] The effects of the micro-Doppler effect on other parameters are represented by the optional multiplier driven by the processor circuit 14 in Figure 1 To mitigate these effects, advanced signal processing techniques can be used. For example, time-frequency analysis techniques can be used to separate the micro-Doppler effect from the overall motion of the target, allowing for more accurate measurement of RCS, range, and angle.
[0069] Device 1 also includes a tunable frequency shift circuit 15, which is used to frequency shift the RF signal 151, e -jωΔτ ·S(jω / A) according to the Doppler frequency shift 152, Δω of the moving object.
[0070] Device 1 also includes an antenna array 16, which is used to transmit the RF signal 161, e -jωτ ·S(j(ω + Δω / A) through the RF channel according to the azimuth angle indication 162, φ and the elevation angle indication 163, θ of the moving object. This can be referred to as electronic beam steering.
[0071] As Figure 1As shown on the left, the device 1 may also include a memory circuit 17 configured to store one or more of the following object parameters: distance indication 122,R of a moving object; cross-sectional area indication 132,RCS of a moving object; velocity indication 141,v of a moving object; azimuth angle indication 162,φ of a moving object; and elevation angle indication 163,θ of a moving object.
[0072] A recording and playback method can also be used. In this method, a specific micro-Doppler type is recorded and then its main Doppler is superimposed on the signal. This allows for an accurate replication of a specific micro-Doppler effect, which is particularly useful for test and verification purposes.
[0073] Therefore, the processor circuit 14 may also be arranged to retrieve a plurality of micro-Doppler frequency shifts 142,Δω from the recording i . Accordingly, the memory circuit 17 may also include the recording. The processor circuit 14 may also be arranged to retrieve a motion description 171 or a signature description 143 of the moving object from the recording as well. The memory circuit 17 may also include these recordings.
[0074] The processor circuit 14 may also be arranged to retrieve a plurality of micro-Doppler frequency shifts 142,Δω according to the motion description 171 (such as swinging, rotating, vibrating, etc.) i The signature may include aspects such as the shape, size, material, and motion of the object, as well as the characteristics of the environment where the object is located. Signatures can be classified, i.e., grouped into different categories based on their characteristics. For example, the motion of a rotating helicopter blade can be classified as "rotational motion", while the motion of a swinging pendulum can be classified as "oscillatory motion". Once the signatures are classified, they are mapped to predefined models. These models represent different types of motion and are designed to mimic the behavior of real-world objects. For example, the "rotational motion" model can simulate the motion of a rotating object, while the "oscillatory motion" model can simulate the motion of an oscillating object.
[0075] The processor circuit 14 may also be arranged to provide the motion description 171 according to the signature description 143 of the moving object (such as a human head, a human arm, a bicycle wheel, etc.) and / or the orientation 144 of the moving object (such as vertical, horizontal, etc.). Accordingly, the memory circuit 17 may also be configured to store one or more of the following object parameters: the signature description 143 of the moving object, and the orientation 144 of the moving object.
[0076] AI (Artificial Intelligence) technology can also be used to create micro-Doppler signatures. For example, generative artificial intelligence (AI) algorithms can be trained on a dataset of different signatures and then generate new signatures that mimic the characteristics of the training data. This can allow for the creation of more complex and realistic micro-Doppler signatures.
[0077] AI models for generating micro - Doppler signatures can be trained using supervised learning, unsupervised learning, or reinforcement learning according to the specific requirements of the task. The following are some options:
[0078] Supervised learning: In this approach, the AI model is trained on a labeled dataset, where each example in the dataset consists of a micro - Doppler signature and its corresponding label. The label can be the type of motion (e.g., "rotation", "oscillation"), the type of object (e.g., "helicopter", "car"), or any other relevant characteristic. The AI model learns to predict the label given a micro - Doppler signature. This can be achieved by using various AI models, such as convolutional neural networks (CNNs), which are particularly effective for pattern - recognition tasks.
[0079] Unsupervised learning: In this approach, the AI model is trained on an unlabeled dataset of micro - Doppler signatures. The model learns to identify patterns or structures in the data without any prior knowledge of the labels. This can be achieved using clustering algorithms or auto - encoding algorithms. Clustering algorithms group similar signatures together, and auto - encoding algorithms learn to reconstruct the input data and can be used to generate new data.
[0080] Reinforcement learning: In this approach, the AI model learns to generate micro - Doppler signatures by interacting with a dynamic environment. The model receives feedback in the form of rewards or punishments based on the quality of the generated signatures and learns to improve its performance over time. This can be achieved by using deep reinforcement learning algorithms, which combine deep - learning techniques with reinforcement learning.
[0081] The training data for these AI models can be obtained from various sources, such as real - world measurements, simulations, or synthetic data generation. The data needs to be pre - processed, and in the case of supervised learning, accurately labeled. The labeling process may involve manual annotation by experts, semi - automatic annotation using rule - based systems, or automatic annotation using other AI models.
[0082] Therefore, the processor circuit 14 can also include a generative AI model for providing a corresponding motion description 171. For example, the training of this AI model can involve supervised learning based on the signature description 143 of the moving object and / or the orientation 144 of the moving object as input data and the motion description 171 as output / label data.
[0083] The processor circuit 14 can also include means for providing a plurality of micro - Doppler frequency shifts 142, Δω iAnother AI model. For example, the training of this other AI model can include, based on the signature description 143 of the moving object and / or the orientation 144 of the moving object as input data, and a plurality of micro-Doppler frequency shifts 142, Δω as output / label data i Supervised learning.
[0084] In an advanced implementation, the RF channel can form part of a plurality of multipath RF channels that differ in one or more object parameters (such as azimuth, elevation, distance, etc.); and the processor circuit 14 can also be arranged to simulate a moving object in each of the plurality of multipath RF channels.
[0085] In another advanced implementation, the moving object can form part of a plurality of moving objects that differ in one or more object parameters; and the processor circuit 14 can also be arranged to simulate each of the plurality of moving objects in each of the corresponding plurality of multipath RF channels.
[0086] Mapping an object to a single or multiple channels refers to the process of allocating different parts or aspects of the object's signal to different channels for processing. This can be done in various ways depending on the specific requirements of the task.
[0087] Single-channel mapping: In this case, the entire signal from the object is processed in a single channel. This is simpler compared to multi-channel processing and requires fewer computational resources. It is suitable for objects with simple motion characteristics that can be adequately represented by a single Doppler frequency shift. For example, a car moving in a straight line at a constant speed can be represented by a single Doppler frequency shift and can thus be processed in a single channel.
[0088] Multi-channel mapping: In this case, different parts or aspects of the object signal are processed in different channels. This allows for a more detailed representation of the object's motion characteristics. For example, a helicopter with rotating blades has complex motion that can be represented by multiple Doppler frequency shifts. By processing the signals from the fuselage and the blades in separate channels, the system can obtain a more accurate representation of the helicopter's motion.
[0089] The advantage of multi-channel mapping is that it allows for a more detailed and accurate representation of complex objects. It can also improve the system's ability to distinguish different objects. For example, a system using multi-channel processing can distinguish a car and a helicopter based on different patterns of Doppler frequency shifts in the signal.
[0090] However, multi-channel mapping also has its drawbacks. Compared to single-channel mapping, it requires more computational resources and may be more complex to implement. It may also be more vulnerable to interference because the signals in different channels can interfere with each other.
[0091] Generally, the choice between single-channel mapping and multi-channel mapping depends on the specific requirements of the task, including the complexity of the object being modeled, the available computing resources, and the required level of accuracy.
[0092] In particular, the multiple micro-Doppler frequency shifts 142, Δω of the respective multipath RF channels i can depend on one or more object parameters.
[0093] Figure 2 Shows method 2 according to the present invention.
[0094] Method 2 is arranged to simulate a moving object in the RF channel, corresponding to device 1 described above.
[0095] Method 2 includes the following steps: receiving 21 the RF signal 121, S(jω).
[0096] Method 2 further includes the following steps: delaying 22 the RF signal 121, S(jω) according to the distance indication 122, R of the moving object.
[0097] Method 2 further includes the following steps: attenuating 23 the RF signal 131, e according to the cross-sectional area indication 132, RCS of the moving object -jωΔτ ·S(jω).
[0098] Method 2 further includes the following steps: determining 24 the Doppler frequency shift 152, Δω according to the velocity indication 141, v of the moving object and the multiple micro-Doppler frequency shifts 142, Δω of the moving object i to determine 24 the Doppler frequency shift 152, Δω.
[0099] Method 2 further includes the following steps: frequency-shifting 25 the RF signal 151, e according to the Doppler frequency shift 152, Δω of the moving object -jωΔτ ·S(jω / A).
[0100] Method 2 further includes the following steps: transmitting 26 the RF signal 161, e through the RF channel according to the azimuth indication 162, φ and elevation indication 163, θ of the moving object -jωτ ·S(j(ω + Δω) / A).
Claims
1. An apparatus for simulating a moving object in a radio frequency (RF) channel, the apparatus comprising: a receiving terminal configured to receive an RF signal; an adjustable delay circuit configured to delay the RF signal according to a distance indication associated with the moving object; an adjustable attenuation circuit configured to attenuate the RF signal according to a cross-sectional area indication associated with the moving object; a processor circuit configured to determine a Doppler shift according to a speed indication associated with the moving object and a plurality of micro-Doppler frequency shifts associated with the moving object; an adjustable frequency shift circuit configured to frequency-shift the RF signal according to the Doppler shift associated with the moving object; and an antenna array configured to transmit the RF signal through the RF channel according to an azimuth indication and an elevation indication associated with the moving object.
2. The apparatus according to claim 1, further comprising: a memory circuit configured to store one or more of the following object parameters: the distance indication associated with the moving object, the cross-sectional area indication associated with the moving object, the speed indication associated with the moving object, the azimuth indication associated with the moving object, and the elevation indication associated with the moving object.
3. The device according to claim 2, wherein The processor circuit is further arranged to retrieve the plurality of micro-Doppler frequency shifts from a record.
4. The apparatus according to claim 3, wherein The memory circuit further includes the record.
5. The device according to claim 2, wherein, The processor circuit is further arranged to retrieve the plurality of micro-Doppler frequency shifts according to a motion description.
6. The device according to claim 5, wherein The processor circuit is further arranged to provide the motion description according to a signature description of the moving object and / or an orientation of the moving object.
7. The device according to claim 6, wherein, The memory circuit is further configured to store one or more of the following object parameters: the signature description of the moving object, and the orientation of the moving object.
8. The apparatus according to claim 6, wherein, The processor circuit includes a generative artificial intelligence model for providing a corresponding motion description.
9. The apparatus according to claim 2, wherein the RF channel forms part of a plurality of multipath RF channels that are different in terms of one or more of the object parameters; and the processor circuit is further arranged to simulate the moving object in each of the plurality of multipath RF channels.
10. The apparatus according to claim 9, wherein the moving object forms part of a plurality of moving objects that are different in terms of one or more of the object parameters; and the processor circuit is further arranged to simulate each of the plurality of moving objects in each of the corresponding plurality of multipath RF channels.
11. The device according to claim 9, wherein, The plurality of micro-Doppler frequency shifts of each multipath RF channel depend on one or more of the object parameters of each multipath RF channel.
12. The apparatus according to claim 1, wherein, The RF signal includes one of a radio detection and ranging (RADAR) signal and a 5th generation (5G) 3GPP RF signal.
13. A method for simulating a moving object in a radio frequency (RF) channel, the method comprising: Receive an RF signal; Delay the RF signal according to a distance indication associated with the moving object; Attenuate the RF signal according to a cross-sectional area indication associated with the moving object; Determine a Doppler shift based on a velocity indication associated with the moving object and a plurality of micro-Doppler frequency shifts associated with the moving object; Frequency-shift the RF signal according to the Doppler shift associated with the moving object; And Transmit the RF signal through the RF channel according to an azimuth indication and an elevation indication associated with the moving object.
14. A system, comprising: The apparatus for simulating a moving object in a radio frequency (RF) channel according to claim 1; And a sensor circuit for classifying the moving object based on an RF signal received from the apparatus.