Radar Clutter Suppression via Frequency Band Segmentation
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Solution Overview
Problem
Existing radar systems face challenges in distinguishing between high frequency clutter returns and target returns, particularly in environments with objects that have significant discontinuities, leading to false detections, as seen in rocky outcrops.
Innovation Solution
A method involving frequency filtering of returns from multiple range cells to estimate and suppress clutter residues by calculating the maximum low frequency clutter value from proximal range cells and applying a predetermined offset for Doppler filtering, which helps in discarding clutter residues and preventing false detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Doppler filtering is used to suppress clutter returns, then low frequency clutter returns can be detected and suppressed, but high frequency clutter returns cannot be distinguished from high frequency target returns
Solution Approach 1:
The patent divides the frequency spectrum into multiple bands (low frequency band and high frequency band) and processes each band separately. Low frequency returns are processed through Doppler filtering to estimate clutter residues, while high frequency returns are processed independently. This segmentation allows the system to apply different processing strategies to different frequency ranges, effectively suppressing low frequency clutter while preserving high frequency target returns.
Solution Approach 2:
The patent introduces an intermediary parameter called 'clutter residue' that is derived from low frequency returns and used to estimate the clutter component in high frequency returns. This clutter residue acts as a mediator that bridges the information from low frequency processing to high frequency clutter suppression, enabling the system to distinguish between clutter and target returns in the high frequency band.
2Reliability
If the method from PCT/GB2008/050663 is used to suppress high frequency clutter, then false detections from strong clutter returns are reduced, but false detections still occur in environments with objects having sizeable discontinuities
Solution Approach 1:
The patent dynamically adjusts the clutter residue estimation by incorporating a maximum search window that adapts to the specific environmental conditions. The system searches for the maximum clutter residue value within a defined window and uses this dynamic estimate to suppress clutter in the current range cell. This dynamic approach allows the system to adapt to complex environments with discontinuous objects, maintaining low false detection rates even when object characteristics vary significantly.
3Device complexity
If clutter residue estimation uses only local range cell data, then processing is simple, but accuracy decreases in environments with strong clutter from discontinuous objects
Solution Approach 1:
The patent performs preliminary processing of low frequency returns from multiple range cells to establish a clutter residue estimate before processing the high frequency returns. By预先 (in advance) characterizing the clutter properties from low frequency data and using this information to guide high frequency clutter suppression, the system achieves more accurate clutter residue estimation without significantly increasing overall processing complexity. The preliminary low frequency analysis provides a foundation that simplifies subsequent high frequency processing.
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 effectively reduces false detections by accurately distinguishing between clutter and target returns, even in complex environments with objects that produce strong returns and have sizeable discontinuities, improving the precision of signal processing in radar systems.
Implementation Method 1
a signal transmitted to detect a target may be returned by a less interesting object
Implementation Method 2
Returns from less interesting objects are known as clutter returns or clutter
Implementation Method 3
Doppler filtering divides a returned signal into a number of frequency bands according to the frequency of the returned signal or according to the frequency shift of the returned signal relative to the transmitted signal. Because the frequency and the frequency shift are related to the velocity of the object or target
Data Source
AI summary
There is disclosed a method for counteracting the effect which crags and other such environmental formations can have on radar returns or returns in similar sensor systems. In particular it has been found that the gaps between crags can lead to false detections because of firstly the function of certain signal processors which compare the high frequency return from a certain cell to a low frequency return from that cell, and secondly the effect of smearing of the returns from one cell to another. The invention seeks to mitigate this effect by selecting the maximum low frequency return from a group of range cells as the high frequency offset.