The deep-coupling of a global navigation satellite system (GNSS) with an inertial navigation system (INS) can provide accurate and reliable navigation information. There are several kinds of deeply-coupled structures. These can be divided mainly into coherent and non-coherent prefilter based structures, which have their own strong advantages and disadvantages, especially in accuracy and robustness. In this paper, the existing pre-filters of the deeply-coupled structures are analyzed and modified to improve them firstly. Then, an adaptive GNSS/ INS deeply-coupled algorithm with hybrid pre-filters processing is proposed to combine the advantages of coherent and non-coherent structures. An adaptive hysteresis controller is designed to implement the hybrid pre-filters processing strategy. The simulation and vehicle test results show that the adaptive deeply-coupled algorithm with hybrid pre-filters processing can effectively improve navigation accuracy and robustness, especially in a GNSS-challenged environment.

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Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration—which are the basis of tracking error estimation—are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (−0.25 cycle, 0.25 cycle) to (−0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz.

In order to reduce the quantization noise of lowresolution DAC, we study a noise shaping technique that can reshape the white quantization noise to an irregular spectrum, in which the noise in the data subcarrier band is almost transformed into the null subcarrier band. Both in simulation and experiment, we verify the effectiveness of the investigated scheme in 25 GHz 16-QAM/32-QAM/64-QAM DMT transmission systems. The experimental results show that the noise shaping technique can enhance the receiver sensitivity of 4-bit quantized 16-QAM DMT and 5-bit quantized 32-QAM DMT by 4.3 dB and 2.5 dB respectively, at BER of hard decision forward error correction (HD-FEC) threshold (3.8×10 -3 ). In addition, with the aid of noise shaping, the performance of 4-bit quantization 16-QAM DMT system is the same as the 8-bit quantization 16-QAM DMT system at the HD-FEC threshold. The experimental results reveal that the proposed noise shaping scheme is a good solution for high-speed, low-cost short reach intra-DCI with low-resolution DAC in future 6G networks evolved from 5G mobile networks.

The global navigation satellite system (GNSS) has been widely used in both military and civil fields. This study focuses on enhancing the carrier tracking ability of the phase-locked loop (PLL) in GNSS receivers for high-dynamic application. The PLL is a very popular and practical approach for tracking the GNSS carrier signal which propagates in the form of electromagnetic wave. However, a PLL with constant coefficient would be suboptimal. Adaptive loop noise bandwidth techniques proposed by previous researches can improve PLL tracking behavior to some extent. This paper presents a novel PLL with an adaptive loop gain control filter (AGCF-PLL) that can provide an alternative. The mathematical model based on second-and third-order PLL was derived. The error characteristics of the AGCF-PLL were also derived and analyzed under different signal conditions, which mainly refers to the different combinations of carrier phase dynamic and signal strength. Based on error characteristic curves, the optimal loop gain control method has been achieved to minimize tracking error. Finally, the completely adaptive loop gain control algorithm was designed. Comparable test results and analysis using the new method, conventional PLL, FLL-assisted PLL, and FAB-LL demonstrate that the AGCF-PLL has stronger adaptability to high target movement dynamic.

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Abstract--In view of the problem of modulation recognition algorithm existing about low recognition rate under environment condition of low SNR, the algorithm of first-order cyclic moment are first presented used in band signal of VHF modulation classification recognition in this paper and the recognition rate increased significantly. The first-order cycle frequencies at which estimated first-order cyclic moment magnitudes exceed the cutoff value were selected as candidate cycle frequencies based on estimation first-order cyclic moment at first-order cycle frequency series, then decided to choose the number of candidate cycle frequency by a cyclostationarity test to realize signal modulation classification recognition, the classification recognition rate can reach more than 98% under condition of SNR is greater than -6 dB.

Passive optical network (PON) is continuously explored for new architectures and effective DSP techniques to adapt to the next generation communication. In this paper, we summarize our work and discuss the challenges and potential solutions for the next-generation PON.