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Gridless Maximum Likelihood One-Bit Direct Position Determination
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PRE
AI
DOI：10.1109/LSP.2024.3491020.png)
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摘要
En 中文
Direct position determination (DPD) (a.k.a. direct localization) offers enhanced precision over traditional two-step approaches. This technique, however, involves considerable communication overhead for transmitting raw data. Low-bit direct localization methods have recently been introduced to address this issue. In this letter, we present a gridless, one-bit maximum likelihood (ML) approach for the direct localization of an orthogonal frequency division multiplexing (OFDM) signal source. A recent majorization-minimization (MM) algorithm introduced a surrogate function for the log-likelihood function, which lacks a closed-form optimal solution and requires exhaustive searches at each iteration. Our method improves upon this algorithm by developing a refined surrogate function that yields a closed-form optimal solution, thereby eliminating the need for exhaustive searches. Accordingly, the proposed MM approach can eliminate grid quantization errors (GQE) by eliminating the search process. Simulation results validate the proposed method's efficacy in mitigating GQE and its efficiency in scenarios with densely populated search grids.
Keyword:
Location awareness
OFDM
Quantization (signal)
Signal processing algorithms
Maximum likelihood estimation
Closed-form solutions
Base stations
Minimization
Upper bound
Time measurement
Direct position determination
majorization-minimization
one-bit quantization
maximum likelihood estimation
localization
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
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