Spread Spectrum Signal Acquisition Across Large Doppler Ranges
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Solution Overview
Problem
Detection of spread spectrum signals is challenging due to Doppler shifts caused by motion of the transmitter or receiver, making it difficult to synchronize and acquire the signal.
Innovation Solution
An architecture for spread spectrum signal detection and acquisition that employs frequency domain matched filtering across a range of Doppler frequencies, using linear convolution and time multiplexed processing banks to handle large Doppler shifts efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency domain matched filtering is used across a range of Doppler frequencies, then detection accuracy over large Doppler ranges is improved, but device complexity increases
Solution Approach 1:
The system divides the Doppler frequency range into multiple segments, with each acquisition processing bank handling a specific segment. Multiple banks operate in parallel to cover the entire range, breaking down the complex task of handling large Doppler shifts into manageable portions while maintaining detection accuracy across all frequencies.
Solution Approach 2:
The patent transitions from time-domain processing to frequency-domain processing using FFT (Fast Fourier Transform). This dimensional change allows the system to efficiently handle Doppler frequency shifts by operating in the frequency domain, where matched filtering can simultaneously process multiple frequency offsets, reducing overall device complexity despite the expanded detection range.
2Productivity
If multiple acquisition processing banks operate in parallel, then processing speed and latency are improved, but device complexity increases
Solution Approach 1:
The system segments the Doppler frequency range and assigns different acquisition processing banks to handle specific segments in parallel. Each bank processes a portion of the frequency spectrum independently, enabling simultaneous processing that reduces latency and improves overall processing speed while distributing the computational load across multiple units.
Solution Approach 2:
Multiple acquisition processing banks are designed with identical, reusable architecture that can be instantiated in parallel. Each bank performs the same correlation and detection functions but operates on different frequency segments, allowing the system to scale processing capacity through replication rather than requiring complex heterogeneous processing units.
3Measurement precision
If linear convolution is used instead of circular convolution, then detection accuracy is improved, but use of energy increases
Solution Approach 1:
The system uses overlapping and saving techniques with periodic processing windows to implement linear convolution through repeated application of circular convolution. By dividing the input signal into overlapping segments and processing each periodically, the system achieves accurate linear convolution results while reusing computational operations across segments, reducing overall energy consumption compared to direct linear convolution implementation.
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
Enables accurate detection and synchronization of spread spectrum signals over large Doppler frequency ranges, reducing latency and resource usage compared to other methods.
Implementation Method 1
When either the transmitter of the signal or the receiver (or both) are in motion, the spread spectrum signal is subject to Doppler shifts which make detection of the preamble more challenging
Data Source
AI summary
Techniques are provided for detection and acquisition of signals. A methodology implementing the techniques according to an embodiment includes correlating an input signal with a code sequence at a first plurality of frequency offsets and generating a first bit vector representing locations of correlation detection peaks for each of the first plurality of frequency offsets; correlating the input signal with the code sequence at a second plurality of frequency offsets and generating a second bit vector representing locations of correlation detection peaks for each of the second plurality of frequency offsets; and generating a combined bit vector and accumulating the combined bit vectors over time. The method also includes identifying two consecutive correlation detection peaks in the accumulated combined bit vectors that are separated by a number of bit locations that correspond to a selected range of Doppler offsets; and generating a signal acquisition detection in response to the identification.