Unified Signal Processing Research Articles

Guest Editorial Special Issue on Integrated Sensing and Communications for Future Green Networks

With the recent advances of wireless communications and signal processing techniques, the capability of wireless sensing would be integrated with communications, which benefits from dedicated communications and sensing hardware and enables new waveform design, transmission strategies, and resource allocation. In particular, a radio emission could simultaneously be used for conveying communication data as well as extracting environmental information from the scattered echoes. It is expected that this emerging paradigm can significantly improve the energy and hardware efficiencies of next generation cellular network and can enable a greener network. In practice, the integration may happen on different levels, via the same hardware architecture, the same spectrum resources, or via a unified signal processing framework such that different kinds of resource efficiency are achieved. This type of research is normally referred to as Integrated Sensing and Communications (ISAC).

On the Use of Reciprocal Filter Against WiFi Packets for Passive Radar

This article derives a novel unified signal processing scheme for WiFi-based passive radar in order to limit its complexity and enhance its suitability for short range civilian applications. To this purpose, the exploitation of a reciprocal filtering (RpF) strategy is investigated as an alternative to conventional matched filtering at the range compression stage. Along with the well-known advantage of a remarkable sidelobes control capability for the resulting range-Doppler response, the use of a RpF is shown to provide additional benefits for the specific sensor subject of this article. Specifically, it allows to streamline the disturbance cancellation stage and to implement a unified signal processing architecture which is capable to handle the different modulation schemes typically adopted in WiFi transmissions. Appropriate adjustments are also proposed to the theoretical RpF in order to cope with the inherent loss in terms of signal-to-noise power ratio. The effectiveness of the proposed signal processing scheme encompassing the RpF strategy is proved against both simulated and experimental datasets.

Time Domain Channel Estimation and Equalization of CP-OTFS Under Multiple Fractional Dopplers and Residual Synchronization Errors

In the last few years, orthogonal time frequency space (OTFS) modulation has received significant attention as an alternative to OFDM especially for high mobilty scenarios. In this work, we develop a delay-Doppler domain embedded pilot based time domain channel estimation for cyclic prefix (CP)-OTFS in the presence of residual frame timing offset, carrier frequency offset and fractional multiple Doppler. One of the reasons for time domain processing is that the time domain channel representation is relatively more sparse as compared to its delay Doppler domain representation in the presence of residual synchronization errors. We also describe a time domain low complexity linear minimum mean square error (MMSE) equalization and successive interference cancellation (SIC) receiver for LDPC (low density parity check) coded CP-OTFS in this work. We further show the impact of residual frame timing offset, carrier frequency offset and fractional multiple Doppler on OTFS symbols. It is seen from the extensive Monte Carlo simulation results that the estimation and compensation methods presented here provide necessary resilience properties to OTFS. We bring out the tolerance of OTFS to such residual synchronization errors. It is further observed that the SIC is able to improve the performance of the system such that it almost matches that of the ideal knowledge based MMSE equalization. We also show the performance of RCP (reduced CP)-OTFS when used with the developed channel estimation and equalization algorithms. A unified signal processing flow for OTFS and orthogonal frequency division multiplexing (OFDM) is also described in this work to motivate studies on coexistence between the two as well as to encourage investigations on a seamless transition between OFDM and OTFS based systems for future adaptive air interface design.

Multirotors Video Synthetic Aperture Radar: System Development and Signal Processing

360-degree video synthetic aperture radar (VideoSAR) presents a powerful capability for the information perception of dynamic scenes. In comparison to time-consuming airborne SAR, miniature SAR (MiniSAR) mounted on an unmanned aerial vehicle platform is a cost-effective configuration that provides a higher operation flexibility for video acquisition. Nevertheless, MiniSAR system development and signal processing limited by multiple factors are still challenging issues, including restricted weight, volume, power consumption, complicated trajectory imaging, and high-efficient video processing. In this article, we develop a multirotors VideoSAR system at X-band in Nanjing University of Aeronautics and Astronautics, concerning hardware architecture, field experiment, and video signal processing. It has the capability of ultrahigh resolution imaging with three available channels up to 1.8-GHz transmission bandwidth. Field programmable gate array-based unified signal processing architecture can further accelerate the generation of massive VideoSAR sequences in terms of both circular spotlight and stripmap modes. Several experimental results have been presented to demonstrate the validity of our developed system.

A unified approach to detecting and trending changes caused by mechanical faults in rotating machinery

For detecting faults in rotating machinery, different fault types generally require different techniques for the effective detection of the faults; hence, many different techniques have been developed. However, we often find that the existing detection techniques are either incapable or ineffective for many new fault types. Therefore, we will need to develop brand new methods after the fault event. This can significantly constrain the usefulness and effectiveness of machine health monitoring systems. In this article, we propose a unified signal processing approach to detecting and trending changes caused by various types of faults in rotating machinery. The theoretical foundation of the proposed technique is based on extracting the differences between the synchronously averaged (angularly resampled) signals acquired under the changing health conditions after aligning their phases. The aligning of the phases is achieved through a novel and efficient approach, which is performed in the frequency domain. The alignment enables a direct comparison between the amplitudes of the synchronously averaged signals and provides a trustworthy evaluation using the same reference datum. The proposed method is novel and conceptually unsophisticated, and its effectiveness is demonstrated using vibration data from rotating machines with several different types of faults. The results have shown that this single unified change detection approach can be very effective in detecting and trending changes caused by many different types of faults in rotating machines. This is an ideal technique to be implemented for testing on aircraft engine onboard health monitoring systems.

A Generalized Machine Fault Detection Method Using Unified Change Detection


 
 
 Many different techniques have been developed for detecting faults in rotating machinery. This is because different fault types typically require different techniques for the effective detection of the fault. However, for many new or unknown fault types, we have found that the existing detection techniques are either incapable or ineffective and that we therefore need to come up with brand new methods after the fault event. This can significantly constrain the usefulness and effectiveness of Prognostic Health Management (PHM) systems. In this paper we attempt to look at detecting global changes in the synchronously averaged signals as the machine’s health status progresses from healthy to faulty, and to define one unified signal processing technique and its associated condition indicators for the detection of changes caused by various types of faults in rotating machinery. The proposed method is conceptually very simple, and its effectiveness is demonstrated using vibration data from machines with several different types of faults. The results have shown that this single unified change detection approach can be very effective in detecting and trending changes caused by many different types of machine faults.