High-Precision Trajectory Data Reconstruction for TT&amp;C Systems Using LS B-Spline Approximation

Sun, Jieyi; Wang, Yongqing; Shen, Yuyao; Lu, Shaozhong

doi:10.1109/lsp.2020.2996091

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…The impulse response of the direct B‐spline filter can be obtained based on the direct spline transform [28]. Moreover, an optimisation criterion can be introduced into the design of the direct B‐spline filter to improve its robustness when the input signal is corrupted with noise [26]. In this study, we choose the latter design method.…”

Section: Doppler‐aided Gnss Position Estimation With B‐spline Smoothi...mentioning

confidence: 99%

“…B‐spline signal processing has a wide ranging applicability, such as sampling rate conversion, filter design, and signal reconstruction [26–30]. The mathematical model of B‐spline signal processing is written as

s (t) = {falsetrue}_{\sum}^{k = - \infty} y [k L] β_{L T_{0}}^{n} (t - k L T_{0})

where t represents continuous time.…”

Section: Underlying Principlesmentioning

confidence: 99%

“…We then derive the mathematical expressions using the Doppler measurements to smooth the code measurements based on B‐spline signal processing. B‐splines are preferred in this study because of their following properties: [26–29]: B‐splines are composed of piecewise polynomials; n th order B‐splines can ensure n th order continuity of the output signal; B‐spline signal processing can be implemented using digital filters, which are simple to integrate with real‐time applications. …”

Section: Introductionmentioning

confidence: 99%

“…We then derive the mathematical expressions using the Doppler measurements to smooth the code measurements based on B-spline signal processing. B-splines are preferred in this study because of their following properties: [26][27][28][29]:…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Doppler‐aided Global Navigation Satellite System position estimation with B‐spline smoothing strategy

Sun

Wang

Shen

2021

IET Radar Sonar & Navi

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Smoothing process can effectively improve the accuracy of the Global Navigation Satellite System (GNSS) position estimation algorithm. In this study, a Doppler‐aided GNSS position estimation algorithm with a B‐spline smoothing strategy is proposed. B‐spline signal processing is used to smoothen the code measurements with Doppler measurements, which were selected because they are more robust and immune to cycle slips than carrier phase measurements. Next, the mathematical expressions of the smoothing process and position estimation are derived. The smoothing process is based on the structure of a digital filter, which is especially suitable for real‐time applications. The Cramer–Rao lower bound of the proposed algorithm is derived. Moreover, a complete implementation structure of the proposed algorithm is presented. The validity of the proposed algorithm is verified through scenario simulation in terms of static, kinematic, and adverse environments. The advantages of the proposed algorithm are demonstrated by comparison with existing algorithms.

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Section: Doppler‐aided Gnss Position Estimation With B‐spline Smoothi...mentioning

confidence: 99%

s (t) = {falsetrue}_{\sum}^{k = - \infty} y [k L] β_{L T_{0}}^{n} (t - k L T_{0})

where t represents continuous time.…”

Section: Underlying Principlesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Doppler‐aided Global Navigation Satellite System position estimation with B‐spline smoothing strategy

Sun

Wang

Shen

2021

IET Radar Sonar & Navi

Self Cite

View full text Add to dashboard Cite

show abstract

“…Under the premise of receiving complete signals, signal restoration can be achieved through techniques such as signal adaptive reconstruction [6], time-domain equalization [7], etc., enabling high-precision detection. However, in practical reception, the equipment side necessitates swift signal transmission for real-time analysis.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Detection Method for Satellite TT&C Signals under Restricted Conditions Based on TATR

Li,

Shi,

Wang

et al. 2024

Remote Sensing

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In complex electromagnetic environments, satellite telemetry, tracking, and command (TT&C) signals often become submerged in background noise. Traditional TT&C signal detection algorithms suffer a significant performance degradation or can even be difficult to execute when phase information is absent. Currently, deep-learning-based detection algorithms often rely on expert-experience-driven post-processing steps, failing to achieve end-to-end signal detection. To address the aforementioned limitations of existing algorithms, we propose an intelligent satellite TT&C signal detection method based on triplet attention and Transformer (TATR). TATR introduces the residual triplet attention (ResTA) backbone network, which effectively combines spectral feature channels, frequency, and amplitude dimensions almost without introducing additional parameters. In signal detection, TATR employs a multi-head self-attention mechanism to effectively address the long-range dependency issue in spectral information. Moreover, the prediction-box-matching module based on the Hungarian algorithm eliminates the need for non-maximum suppression (NMS) post-processing steps, transforming the signal detection problem into a set prediction problem and enabling parallel output of the detection results. TATR combines the global attention capability of ResTA with the local self-attention capability of Transformer. Experimental results demonstrate that utilizing only the signal spectrum amplitude information, TATR achieves accurate detection of weak TT&C signals with signal-to-noise ratios (SNRs) of −15 dB and above (mAP@0.5 > 90%), with parameter estimation errors below 3%, which outperforms typical target detection methods.

show abstract

Multisegment optimization design of variable fractional-delay FIR filters

Sun

Wang

Shen

et al. 2021

Digital Signal Processing

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High-Precision Trajectory Data Reconstruction for TT&C Systems Using LS B-Spline Approximation

Cited by 4 publications

References 17 publications

Doppler‐aided Global Navigation Satellite System position estimation with B‐spline smoothing strategy

Doppler‐aided Global Navigation Satellite System position estimation with B‐spline smoothing strategy

Intelligent Detection Method for Satellite TT&C Signals under Restricted Conditions Based on TATR

Multisegment optimization design of variable fractional-delay FIR filters

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