Radar Fill Level Detection for Rail Logistics Yards
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Solution Overview
Problem
Existing methods for determining the filling level in route-bound vehicle logistics systems, such as marshalling yards, require contact-based technical aids and cannot accurately record vehicle positions or detect gaps between vehicles, limiting their effectiveness.
Innovation Solution
The method employs imaging radar technology with a combination of antenna elements arranged in a vertical distance to emit and receive radar waves, transforming signal data into 2D radar signature images for fully automatic image processing, enabling contactless detection and classification of vehicles, including their positions and types, using change analysis and polarization properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If contact-based technical aids (trigger relays, counting devices) are installed along routes to detect vehicles, then vehicle counting and fill level determination can be achieved, but the system complexity increases and requires additional infrastructure installation
Solution Approach 1:
The patent replaces mechanical contact-based detection systems (trigger relays, counting devices) with radar technology that uses electromagnetic waves to detect vehicles. The radar unit transmits radar waves that reflect off vehicles, and the reflected waves are received and processed to determine vehicle presence, position, and movement without any physical contact or infrastructure installation along the route.
Solution Approach 2:
The patent introduces radar waves as an intermediary medium to detect vehicles. Instead of direct mechanical interaction between detection devices and vehicles, the radar waves serve as a mediator that carries information about vehicle presence, position, and motion from the detection point to the processing system.
2Measurement precision
If Doppler radar technology is used to detect moving vehicles, then vehicle detection is possible, but stationary vehicles cannot be detected since they do not generate Doppler signals
Solution Approach 1:
The patent transitions from a dynamic detection method (Doppler effect requiring motion) to a static detection capability by analyzing the spatial distribution and reflection characteristics of radar waves. The system evaluates the amplitude, phase, and temporal patterns of reflected radar signals to distinguish between moving and stationary vehicles, and to detect their positions regardless of motion state.
3Loss of information
If individual vehicle detection is implemented using radar, then fill level information can be obtained, but additional technical aids must be installed along each route
Solution Approach 1:
The patent employs a universal radar-based detection system that can monitor multiple routes and detect various vehicle characteristics (position, speed, direction, type) using a single type of detection technology. The radar unit can be positioned to monitor one or multiple routes simultaneously, eliminating the need for route-specific detection infrastructure.
4Measurement precision
If radar waves are transmitted and received continuously to obtain chronological time series data, then accurate vehicle position and movement information can be obtained, but energy consumption increases
Solution Approach 1:
The patent implements periodic radar signal transmission and reception to obtain chronological time series data of reflected radar waves. By transmitting radar waves at regular intervals and analyzing the temporal patterns of reflected signals, the system accurately determines vehicle position, movement, and acceleration while managing energy consumption through controlled transmission cycles.
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 approach allows for a fully automatic, contactless determination of the filling level and vehicle classification, providing accurate occupancy information and identifying vehicle types without the need for additional technical aids along the routes, and is scalable for large logistics systems.
Implementation Method 1
at least one radar unit (4) installed at a vertical distance above the at least one route to be monitored... emit radar waves and receive radar waves reflected along the at least one route to be monitored
Implementation Method 2
the radar signal data sets are transformed into a time series of 2D radar signature images as part of signal processing
Data Source
Figure 1~2
Figure 3~4
Figure 5~6b
AI summary
The invention relates to a method for determining the fill level of a track-bound logistics installation providing intermediate storage for self-powered or externally powered vehicles, in particular in the form of a switching or shunting yard having railway cars arranged along a track installation, wherein, by means of radar technology, the vehicles are detected along at least one track of the logistics installation which is to be monitored, and the fill level is determined, that is, at least a number of vehicles along the at least one track to be monitored is determined, and represented. The method is characterized according to the solution by the combination of the following method steps: arranging at least one radar unit having a transmission and reception lobe region at a vertical distance (a) above the at least one track such that the at least one track to be monitored is located within the transmission and reception lobe region of the at least one radar unit; emitting radar waves and receiving radar waves reflected along the at least one track to be monitored in order to obtain a time series of radar signal data records, which contain the respective image information of the at least one track to be monitored at respective different times; processing the radar signal data records in order to obtain a time series of 2-dimensional radar signature images; carrying out a change analysis comparing at least two radar signature images selected from the times series in order to obtain a radar signature difference image; localizing and classifying vehicles at least on the basis of the radar signature difference image; and converting the localized and classified vehicles into a schematic diagram representing the logistics installation.