Coded Radar Signal Encoding for NLOS Object Detection
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Solution Overview
Problem
Existing radar systems for autonomous vehicles and Automated Driver Assist Systems (ADASs) face challenges in accurately detecting objects both within and outside the line-of-sight (LOS) due to obstructions like buildings and trees, which obstruct direct transmission paths and cause signal reflections or deflections, leading to interference and reduced detection capabilities in non-line-of-sight (NLOS) areas.
Innovation Solution
The implementation of a coded radar system using steerable beamforms and metastructure antennas, combined with advanced signal processing techniques like Pulse Code Modulation (PCM) and Frequency-Modulated Continuous Wave (FMCW) modulation, enables reliable object detection by encoding signals to differentiate between direct and reflected transmissions, and employing metastructures to manage electromagnetic energy effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional radar systems transmit electromagnetic signals for object detection, then detection coverage is provided, but signal interference and detection accuracy deteriorate in non-line-of-sight areas due to obstructions and reflections
Solution Approach 1:
The patent applies parameter changes by modulating radar signals with unique codes (e.g., pseudo-random codes) and varying signal characteristics such as frequency, phase, and time delay. This allows the system to distinguish between direct and reflected signals by analyzing changes in signal parameters, thereby reducing interference and improving detection reliability in non-line-of-sight areas.
Solution Approach 2:
The patent uses coded signals as an intermediary mechanism to differentiate between direct and reflected electromagnetic waves. By embedding unique codes and temporal patterns in the transmitted signals, the system can identify and separate useful reflections from harmful interference, enabling reliable detection despite obstructions.
2Adaptability or versatility
If radar signals are transmitted to detect objects in obstructed environments, then detection capability is maintained, but measurement precision deteriorates due to signal reflections and deflections
Solution Approach 1:
The patent employs preliminary action by pre-coding transmitted signals with known patterns and sequences before transmission. The receiver then correlates received signals with the expected coded patterns to identify direct paths versus reflections. This preliminary encoding allows the system to anticipate and filter out reflected signals, maintaining precision even in obstructed environments.
Solution Approach 2:
The system uses feedback mechanisms by continuously analyzing the temporal and spectral characteristics of received signals and comparing them against the transmitted coded patterns. This feedback loop enables real-time differentiation between direct and reflected signals, allowing the system to adapt to changing environmental conditions while maintaining measurement precision.
3Ease of operation
If conventional radar systems are used for autonomous vehicle detection, then basic object detection is provided, but decision-making reliability deteriorates due to inaccurate range and velocity information in NLOS areas
Solution Approach 1:
The patent segments the detection problem by separately analyzing different signal components - direct signals versus reflected signals - and processing them through distinct evaluation paths. This segmentation allows the system to identify which detected objects are reliable (direct signals) and which require caution or alternative interpretation (reflected signals), thereby improving decision-making reliability for autonomous driving.
Solution Approach 2:
The patent adds temporal and spectral dimensions to the traditional spatial detection by analyzing signal codes, time delays, and frequency shifts. This dimensional expansion allows the system to distinguish between direct and reflected paths in addition to spatial information, providing richer data for more reliable autonomous driving decisions in complex environments.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enhances the ability to detect objects in both LOS and NLOS areas, improving the accuracy and reliability of object detection, even in dynamic and obstructed environments, by effectively filtering noise and interference, and providing range and velocity information for enhanced decision-making in autonomous driving systems.
Implementation Method 1
a signal is transmitted to communicate information or identify a location of an object... electromagnetic millimeter wavelength transmissions, an antenna transmits signals as a beamform... obstacles that obstruct the direct transmission, such as buildings, trees, and so forth; these obstructions may act as reflection or deflection points that change the direction of all or some of the transmission signal
Data Source
AI summary
Examples disclosed herein relate to a system of object detection, the system including a continuous modulation signal unit to generate a continuous modulation signal, a code generation unit to sample, quantize and encode the continuous modulation signal to generate an encoded signal, a transmit antenna to transmit the encoded signal, and a receive antenna to receive a reflection of the encoded signal and separate the reflection of the encoded signal from other signals.