Basic Principle of Radar Sensing
The core of radar sensing technology is to use the transmission and reception of electromagnetic waves to sense target objects. Its working process can be briefly described as follows: The radar emits electromagnetic waves with specific frequencies and waveforms into space. When these electromagnetic waves encounter an object, part of them will be reflected back, and the radar receives the reflected waves. By measuring the time delay between the transmitted wave and the echo, and based on the characteristic that electromagnetic waves propagate at approximately the speed of light in the air, the distance between the object and the radar can be calculated. For example, in a common automotive millimeter-wave radar, it emits millimeter waves in frequency bands such as 24GHz or 77GHz. If the time delay between the transmitted wave and the echo is t, then the object distance d = c×t/2 (where c is the speed of light).
In addition to the distance, the radar can also obtain the speed information of the object. This is based on the Doppler effect. When an object moves relative to the radar, the frequency of the echo will change. If the object moves towards the radar, the echo frequency increases; conversely, when it moves away, the frequency decreases. By precisely measuring the amount of frequency change (i.e., the Doppler shift), the radial velocity of the object can be calculated. For example, traffic speed measurement radars use this principle to accurately measure the driving speed of vehicles.
Process of Radar Sensing for Object Trajectory Analysis
Data Collection: The radar continuously transmits and receives electromagnetic waves, obtaining data such as the distance, speed, and angle of the object at different moments. The data points at multiple moments form the original information set of the object's movement. For example, in the air traffic control radar system at an airport, the aircraft in the airspace will be scanned multiple times per second, obtaining a large number of data points about the aircraft's position and speed.
Data Processing and Target Recognition: The received original data contains various noises and interferences, and operations such as denoising and filtering need to be carried out through signal processing algorithms. Then, target recognition algorithms are used to distinguish the objects of interest from the background clutter. In military radars, complex algorithms will be used to identify different targets such as fighter jets and missiles to avoid misjudgment.
Trajectory Calculation and Prediction: Based on a series of continuously timed data points, trajectory calculation algorithms are used to determine the trajectory of the object. A common algorithm is the Kalman filter, which can comprehensively consider the object's motion state (position, speed, etc.) and measurement noise to make an optimal estimate of the object's true trajectory. Moreover, based on the existing trajectory data and the object's motion characteristics, the future motion trajectory of the object can also be predicted. For example, in an autonomous vehicle, the on-board radar calculates the trajectories of surrounding vehicles to predict their positions in the next few seconds, providing a basis for the vehicle's driving decision-making.
Practical Application Scenarios
Transportation Field
Intelligent Transportation System (ITS): On urban roads, radar sensors installed at intersections or road sections can monitor the driving trajectories of vehicles in real time. By analyzing the trajectory data of a large number of vehicles, the traffic management department can understand the distribution of traffic flow, the changes in vehicle driving speed, etc., so as to optimize the timing of traffic lights and relieve congestion. For example, on the main roads of some large cities, radar sensing technology has been used to achieve dynamic traffic signal control, adjusting the duration of traffic lights according to the real-time traffic flow, which improves the road traffic efficiency.
Autonomous Driving: The on-board radar is one of the key sensors of an autonomous vehicle. It can accurately sense the trajectories of surrounding vehicles, pedestrians, obstacles and other objects, providing basic information for the vehicle's decision-making and planning system. For example, the millimeter-wave radar equipped in Tesla cars can monitor the movement of objects in the surrounding environment in real time, helping the vehicle to achieve functions such as automatic following, lane change assistance, and collision warning, ensuring driving safety.
Security Monitoring
Perimeter Protection: Radar sensing devices are deployed around important facilities (such as military bases, prisons, large warehouses, etc.). When a person or an object intrudes into the protected area, the radar can detect its movement trajectory, issue an alarm in a timely manner, and can be linked with a camera for target tracking and image acquisition. For example, in the perimeter security systems of some airports, radar is used to accurately monitor the movement trajectories of illegal intruders. Combined with surveillance cameras, it enables a rapid response and accurate handling of intrusion behaviors.
Behavior Analysis: In public places (such as shopping malls, railway stations, etc.), radar sensing can be used to analyze the movement trajectories of people. By analyzing the trajectories of the crowd, the degree of congestion in the place can be evaluated, the spatial layout and guidance signs can be optimized, and the efficiency and safety of people's passage can be improved. For example, large shopping malls use radar sensing technology to analyze the walking trajectories of customers in different areas, adjust the store layout and product display, so as to improve the customer shopping experience and sales volume.
Industrial Monitoring
Logistics Automation: In an automated logistics warehouse, radar sensors are used to monitor the trajectories of goods handling robots (AGVs) and goods on the conveyor belt. It ensures that the AGVs travel along the predetermined path, avoids collisions, and monitors the transportation status of goods in real time. For example, Amazon's smart logistics warehouse makes extensive use of radar sensing technology to achieve precise control of the goods transportation process, improving the logistics and distribution efficiency.
Industrial Equipment Operation Monitoring: For some large rotating equipment (such as the blades of wind turbines, industrial centrifuges, etc.), the radar can monitor the trajectories of their key components. By analyzing the trajectory data, potential faults of the equipment can be detected in a timely manner, such as problems like blade deformation and eccentricity. For example, in a wind farm, radar sensing technology is used to conduct long-term monitoring of the wind turbine blades, providing early warning of blade faults, reducing maintenance costs and downtime.
