Stepped LFM Radar Profile for Side Lobe Suppression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Non-contact sensors face challenges in accurately measuring fluid velocity and distance in open channels due to significant signal loss when emitting signals slantwise, leading to errors in calculating volumetric flow rate, especially when velocity and level measurements are not taken at the same point.
Innovation Solution
The development of a stepped Linear Frequency Modulated (LFM) radar/sonar modulation profile, such as the 'Gladkova type' and 'polyphase minaret' profiles, which optimize signal emission and reception to minimize side lobes and aliasing, allowing for precise multi-scale spectral analysis and simultaneous measurement of fluid velocity and distance at a single point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signals are emitted slantwise to the fluid surface for velocity measurement, then fluid velocity can be measured, but significant signal loss occurs because most incident energy glances off the fluid surface
Solution Approach 1:
The patent combines velocity and distance measurements at a single point by using a single antenna to alternately emit CW signals for velocity measurement and FMCW signals for distance measurement, eliminating the need for separate slantwise and perpendicular measurement systems
Solution Approach 2:
The system uses periodic alternation between emitting CW signals for velocity measurement and FMCW signals for distance measurement through a single antenna, allowing both measurements to be performed at the same location without continuous signal loss
2Measurement precision
If signals are emitted perpendicular to the fluid surface for distance measurement, then strong return signal is obtained for required distance accuracy, but velocity measurement at the same point becomes impossible
Solution Approach 1:
A single antenna is designed to perform multiple functions by alternately emitting different types of signals: CW signals for velocity measurement and FMCW signals for distance measurement, making the antenna universal for both measurement purposes at the same location
Solution Approach 2:
The system dynamically switches between different signal types (CW and FMCW) emitted by the same antenna depending on whether velocity or distance measurement is being performed, allowing adaptability for both measurement modes at a single point
3Measurement precision
If stepped LFM sequences are used for FMCW ranging, then range measurement is achieved, but high amplitude side lobe signals and aliasing occur during spectral analysis
Solution Approach 1:
The patent applies non-linear frequency stepping patterns (such as Gladkova type and polyphase minaret profiles) instead of uniform frequency steps, changing the frequency distribution parameters to suppress side lobe amplitudes and reduce aliasing in the spectral analysis
Solution Approach 2:
The patent converts the potentially harmful uniform frequency stepping that causes high side lobes into a beneficial non-linear frequency distribution that suppresses side lobes, turning the problem of frequency step selection into a solution for side lobe reduction
4Productivity
If conventional FMCW schemes are implemented with multi-scale analysis, then computational effort is reduced, but interference from high amplitude side lobes and aliasing prevents correct sensor operation
Solution Approach 1:
The patent changes the frequency modulation parameters from uniform stepped LFM to non-linear frequency profiles (Gladkova type, polyphase minaret) that are specifically designed to work with multi-scale spectral analysis, enabling both computational efficiency and reliable operation by suppressing side lobes and aliasing
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 enhances the precision and resolution of fluid velocity and distance measurements while reducing computational effort and power consumption, enabling accurate volumetric flow rate calculations with improved range resolution and reduced side lobe interference.
Implementation Method 1
Non-contact sensors often emit energy signals such as one or more acoustic or electromagnetic signals toward an object. By analyzing the reflected signals, distance and velocity of the object may be determined. Examples of non-contact sensors include, for example, sonar, radar, laser, and UV devices.
Implementation Method 2
When measuring velocity of a flowing fluid, the signal must typically be emitted slantwise to the fluid surface... A continuous wave (CW) signal for velocity is emitted in a slant wise fashion to the fluid being measured
Implementation Method 3
Recently, Frequency Modulated Continuous Wave (FMCW) radar systems have been designed which are capable of measuring fluid depth and velocity in open channels... A frequency modulated (FMCW) signal for distance is emitted perpendicular to the fluid
Implementation Method 4
The demodulated IF signal may be digitized and analyzed via spectral analysis to determine information about the target, e.g., distance, velocity, etc. Spectral analysis refers to the analysis of the demodulated IF signal with respect to frequency, rather than time. This is often accomplished by calculating the signal's discrete Fourier transform (DFT), for example, via a fast Fourier transform algorithm or FFT.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method for constructing a frequency profile of an emitted signal suitable for use in a non-contact ranging system with multi-scale spectral analysis includes determining N stepped frequency chirps, wherein each frequency chirp of the N stepped frequency chirps has a linear FM modulation of predetermined bandwidth and slope, and wherein a starting frequency for each of the plurality of stepped frequency chirps is chosen so that a non-linear step profile is created which extends over a predetermined total bandwidth, sorting the plurality of N stepped frequency chirps into P sub-sequences, where P is equal to the product of decimation factors to be used in the multi-scale spectral analysis, and ordering the P sub-sequences end to end in time.