Multi-Target Detection in CDMA Radar via Iterative Signal Subtraction
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Solution Overview
Problem
CDMA radar systems face challenges in multi-target detection due to high cross-correlation levels and interference among reflections, which reduce detection range and accuracy, making it difficult to distinguish between multiple targets.
Innovation Solution
The method involves using multiple iterative processing chains in receivers to apply matched filters with different codes, perform Fast Fourier Transforms in the Doppler domain, and subtract the strongest reflection's contribution to isolate and remove cross-correlation effects, allowing for sequential detection of multiple targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If CDMA radar systems use multiple transmitters with different codes simultaneously, then the radar system can achieve improved detection capability and coverage, but high cross-correlation levels and interference among reflections occur, reducing detection range and accuracy
Solution Approach 1:
The received signal processing is divided into T separate processing chains, each corresponding to a different transmitter code. Each processing chain independently processes signals using its specific matched filter, segmenting the complex multi-target detection problem into manageable parts that can be handled separately while maintaining overall system performance.
Solution Approach 2:
The strongest reflection component is extracted and identified from the received signal in each processing chain. By detecting the object with the strongest reflection first and then subtracting its contribution, the method removes the dominant interference component, allowing weaker targets to be detected subsequently.
2Adaptability or versatility
If multiple transmitters transmit different codes simultaneously in a CDMA radar system, then the system can perform multi-target detection, but cross-correlation interference among reflections makes it difficult to distinguish between multiple targets
Solution Approach 1:
The method performs preliminary detection to identify the strongest reflection and its corresponding target before processing other targets. By detecting the object with the strongest reflection first and subtracting its contribution in advance, the system prepares the signal for subsequent detection of weaker targets, making multi-target discrimination feasible.
Solution Approach 2:
The iterative processing chains use feedback from each iteration to improve detection. The result of the subtraction from previous iterations is fed back into the processing chain, allowing the system to progressively refine target detection by removing detected targets' contributions and detecting remaining targets in subsequent iterations.
3Measurement precision
If iterative processing chains are implemented to remove cross-correlation effects, then detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The complex signal processing is segmented into T parallel processing chains, each handling a specific transmitter's code. This segmentation allows independent processing of each code's contributions, simplifying the overall complexity by breaking down the monolithic processing task into manageable, parallelizable units.
Solution Approach 2:
The method implements a limited number of iterations (T iterations for T transmitters) rather than attempting to process all possible target combinations. By performing a finite, predetermined number of iterations where each iteration detects and removes one strongest reflection, the system achieves sufficient detection accuracy without excessive processing complexity.
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 cross-correlation interference, enabling the detection of multiple targets by iteratively removing the strongest reflection's signal and side lobes, thereby enhancing the radar system's dynamic range and accuracy in identifying objects.
Implementation Method 1
applying a matched filter, at each of the T processing chains, with a different one of the different codes
Implementation Method 2
performing a fast Fourier transform (FFT) in a Doppler domain on an output of the matched filter
Implementation Method 3
receiving, at each receiver among one or more receivers, a received signal that includes reflections resulting from transmissions by all of the transmitters
Data Source
AI summary
A system and method to perform multi-target detection in a code division multiple access (CDMA) radar system involve transmitting, from each transmitter among T transmitters, a transmitted signal with a different code, and receiving, at each receiver among one or more receivers, a received signal that includes reflections resulting from each of the transmitted signals with the different codes. The method includes processing the received signal at each of the one or more receivers by implementing T processing chains. Each of the T processing chains is iterative. The method also includes detecting an object at each completed iteration at each of the T processing chains, and subtracting a subtraction signal representing a contribution of the object to the received signal prior to subsequent iterations.