Multi-Layer Overlapped Subaperture Algorithm for Extremely-High-Squint High-Resolution Wide-Swath SAR Imaging with Continuously Time-Varying Radar Parameters

Extremely-high-squint (EHS) geometry of the traditional constant-parameter synthetic aperture radar (SAR) induces non-orthogonal wavenumber spectrum and hence the distortion of point spread function (PSF) in focused images. The method invented to overcome this problem is referred to as new-concept parameter-adjusting SAR. It corrects the PSF distortion by adjusting radar parameters, such as carrier frequency and chirp rate, based on instant data acquisition geometry. In this case, the characteristic of signal is quite different from the constant-parameter SAR and therefore, the traditional imaging algorithms cannot be directly applied for parameter-adjusting SAR imaging. However, the existing imaging algorithm for EHS parameter-adjusting SAR suffers from insufficient accuracy if a high-resolution wide-swath (HRWS) performance is required. Thus, this paper proposes a multi-layer overlapped subaperture algorithm (ML-OSA) for EHS HRWS parameter-adjusting SAR imaging with three main contributions: First, a more accurate signal model with time-varying radar parameters in high-squint geometry is derived. Second, phase errors are compensated with much higher accuracy by implementing multiple layers of coarse-to-fine spatially variant filters. Third, the analytical swath limit of the ML-OSA is derived by considering both the residual errors of signal model and phase compensations. The presented approach is validated via both the point- and extended-target computer simulations.

Compressed Sensing Imaging with Compensation of Motion Errors for MIMO Radar

Using a multiple-input-multiple-output (MIMO) radar for environment sensing is gaining more attention in unmanned ground vehicles (UGV). During the movement of the UGV, the position of MIMO array compared to the ideal imaging position will inevitably change. Although compressed sensing (CS) imaging can provide high resolution imaging results and reduce the complexity of the system, the inaccurate MIMO array elements position will lead to defocusing of imaging. In this paper, a method is proposed to realize MIMO array motion error compensation and sparse imaging simultaneously. It utilizes a block coordinate descent (BCD) method, which iteratively estimates the motion errors of the transmitting and receiving elements, as well as synchronously achieving the autofocus imaging. The method accurately estimates and compensates for the motion errors of the transmitters and receivers, rather than approximating them as phase errors in the data. The validity of the proposed method is verified by simulation and measured experiments in a smoky environment.

Azimuth Multichannel Reconstruction Based on Advanced Hyperbolic Range Equation

To acquire high-resolution wide-swath (HRWS) imaging capacity, the displaced phase center multichannel azimuth beam (DPCMAB) technology is usually adopted in spaceborne synthetic aperture radar (SAR), while multichannel reconstruction must be carried out before imaging process due to azimuth nonuniform sampling. Up to now, almost all azimuth multichannel reconstruction algorithms have been mainly based on conventional hyperbolic range equation (CHRE), but the accuracy of the CHRE model is usually not suitable for the HRWS mode, especially for high resolution and large squint observation cases. In this study, the azimuth multichannel signal model based on the advanced hyperbolic range equation (AHRE) is established and analyzed. The major difference between multichannel signal models based on CHRE and AHRE is the additional time-varying phase error between azimuth channels. The time-varying phase error is small and can be ignored in the monostatic DPCMAB SAR system, but it must be considered and compensated in the distributed DPCMAB SAR system. In addition to the time-varying phase error, additional Doppler spectrum shift and extended Doppler bandwidth should be considered in the squint case during azimuth multichannel reconstruction. The azimuth multichannel reconstruction algorithm based on AHRE is proposed in this paper. Before multichannel reconstruction and combination, time-varying phase errors between azimuth channels were first compensated, and the range-frequency-dependent de-skewing function was derived to remove the two-dimension (2D) spectrum tilt to avoid azimuth under-sampling. Then, azimuth multichannel data were reconstructed according to the azimuth multichannel impulse response based on AHRE. Finally, the range-frequency dependent re-skewing function was introduced to recover the tilted 2D spectrum. Simulation results on both point and distributed targets validated the proposed azimuth multichannel reconstruction approach.

Algorithm for Estimation of Signal Carrier Frequency by Distributed Sync Combination, Optimal According to the Criterion of the Minimum Mean Square Error

An algorithm for accurate estimation of the carrier frequency, which is optimal by the criterion of the min-imum mean square error, is developed which is implemented using relatively short sync combinations distributed over the duration of the packet. The results of the dependence of the accuracy of estimating the carrier frequency on the level of channel noise are presented. Analytical expressions are obtained for an accurate estimate of the frequency and phase errors obtained on the basis of sufficiently short sync combinations. The results of simulation are demon-strated. The research results can be used in satellite radio links with packet data transmission.

Analysis and correction of meteorological disturbance observed by ground radars in complex environment

Ground radar interferometry technology, as a new tool for active remote sensing, has been widely used in the detection of a variety of targets, including landslides, bridges, mines, and dams. This technique usually employs a continuous observation mode with no space baseline. The detection accuracy is mainly affected by meteorological disturbances and noise in the observation environment. In a complex observation environment, meteorological disturbances can lead to phase errors of 10 mm or more, and the effects are different in the range and azimuth directions; this can seriously affect the accuracy of the measurement. In this paper, we analyze the spatial distribution of the phase of meteorological disturbances based on radar monitoring experiments in a complex environment, and propose a correction method that reduces the atmospheric disturbance phase to less than 0.6 mm and effectively improves radar observation accuracy.

PRACTICALAPPLICATION OF SIX SIGMA DMAIC METHODOLOGY IN EVALUATION OF PRE-ANALYTICAL QUALITY INDICATORS IN LABORATORY SETTINGS

The Six Sigma is a global management methodology that empowers clinical laboratories by better understanding of the quality in their laboratories and helps in improving quality and subsequently reducing laboratory costs. The objective of this prospective study was to practically apply Six Sigma on pre-analytical quality indicators i.e. pre-analytical phase errors of “Total Testing Process” in laboratory at PGIMER Satellite Centre, Sangrur (Punjab). In this study Six Sigma DMAIC ( Dene, Measure, Analyse, Improvement and Control) methodology was applied on routine Outpatient Department (OPD) samples received in hematology and biochemistry laboratory from May, 2020 to July, 2020 after institutional ethical committee permission. Pre-analytical phase errors were taken as pre-analytical quality indicators and were broadly classied in to requisition form and sampling errors. Sigma values and frequencies were calculated using Westgard formula present online at (www. westgard.com > six sigma calculators) for pre-analytical phase errors. After that Improvement phase of DMAIC methodology was done by training of laboratory technicians or personell involved in pre-analytical phase by audio-visual aids. Six Sigma values were calculated again after improvement phase. A total of 787 requisition forms and 1105 samples were studied before improvement phase and 889 requisition forms and 1400 samples were studied after improvement phase. Before improvement phase, overall requisition form errors were working at 2.9 sigma and sampling process was working at 3.1 sigma but after improvement phase, requisition form errors were working at 3.3 sigma and sampling process was working at 3.5 sigma. Before and after improvement phase the sample rejection rate in laboratory improved from 1.90% to 0.93% highlighting the benecial concept of six sigma in laboratory in pre-analytical phase leading to increased clinicians and patients'satisfaction and prevents unusual delaying of reports.

Monitoring of Energy Data with Seamless Temporal Accuracy Based on the Time-Sensitive Networking Standard and Enhanced μPMUs

In the energy sector, distributed synchronism and a high degree of stability are necessary for all real-time monitoring and control systems. Instantaneous response to critical situations is essential for the integration of renewable energies. The most widely used standards for clock synchronisation, such as Network Time Protocol (NTP) and Precision Time Protocol (PTP), do not allow for achieving synchronised simultaneous sampling in distributed systems. In this work, a novel distributed synchronism system based on the Time-Sensitive Networking (TSN) standard has been validated for its integration in an architecture oriented towards the high-resolution digitisation of photovoltaic (PV) generation systems. This method guarantees a time stamping with an optimal resolution that allows for the analysis of the influence of fast-evolving atmospheric fluctuations in several plants located in the same geographical area. This paper proposes an enhanced micro-phasor measurement unit (μPMU) that acts as a phasor meter and TSN master controlling the monitoring system synchronism. With this technique, the synchronism would be extended to the remaining measurement systems that would be involved in the installation at distances greater than 100 m. Several analyses were carried out with an on-line topology of four acquisition systems capturing simultaneously. The influence of the Ethernet network and the transducers involved in the acquisition process were studied. Tests were performed with Ethernet cable lengths of 2, 10, 50, and 75 m. The results were validated with 24-bit Sigma-Delta converters and high-precision resistor networks specialised in high-voltage monitoring. It was observed that with an appropriate choice of sensors and TSN synchronism, phase errors of less than ±1μs can be guaranteed by performing distributed captures up to 50 kS/s. Statistical analysis showed that uncertainties of less than ±100 ns were achieved with 16-bit Successive Approximation Register (SAR) converters at a moderate cost. Finally, the requirements of the IEEE C37.118.1-2011 standard for phasor measurement units (PMU) were also satisfied. This standard establishes an uncertainty of ±3.1 μs for 50 Hz systems. These results demonstrate the feasibility of implementing a simultaneous sampling system for distributed acquisition systems coordinated by a μPMU.

Optimum Elements Selection in IRS-Assisted UAV Communications with Phase Errors

<div>This letter considers minimizing the bit error rate (BER) of unmanned aerial vehicle (UAV) communications assisted by intelligent reflecting surfaces (IRSs). By noting that increasing the number of IRS elements in the presence of phase errors does not necessarily improve the BER, it is crucial to use only the elements that contribute to reducing the BER. Consequently, we propose an efficient algorithm to activate only the elements that improve the BER. The proposed algorithm has lower complexity and comparable BER to the optimum selection process, which is an NP-hard problem. The accuracy of the estimated phase is evaluated by deriving the probability distribution function (PDF) of the least-square (LS) channel estimator, and showing that the PDF can be closely approximated by the von Mises distribution at high signal-to-noise ratios (SNRs). The obtained analytical and simulation results show that using all the available reflectors can significantly deteriorate the BER, and thus, elements’ selection is necessary. In particular scenarios, using about 26% of the reflectors provides more than 10 fold BER reduction.</div>

Optimum Elements Selection in IRS-Assisted UAV Communications with Phase Errors

<div>This letter considers minimizing the bit error rate (BER) of unmanned aerial vehicle (UAV) communications assisted by intelligent reflecting surfaces (IRSs). By noting that increasing the number of IRS elements in the presence of phase errors does not necessarily improve the BER, it is crucial to use only the elements that contribute to reducing the BER. Consequently, we propose an efficient algorithm to activate only the elements that improve the BER. The proposed algorithm has lower complexity and comparable BER to the optimum selection process, which is an NP-hard problem. The accuracy of the estimated phase is evaluated by deriving the probability distribution function (PDF) of the least-square (LS) channel estimator, and showing that the PDF can be closely approximated by the von Mises distribution at high signal-to-noise ratios (SNRs). The obtained analytical and simulation results show that using all the available reflectors can significantly deteriorate the BER, and thus, elements’ selection is necessary. In particular scenarios, using about 26% of the reflectors provides more than 10 fold BER reduction.</div>

Research on Quantization Error Influence of Millimeter-Wave Phased Array Antenna

The millimeter-wave phased array antenna is a higher integration system that is composed of different subarray modules, and in actual engineering, the existing amplitude, phase errors, and structural errors will change the performance of the array antenna. This paper studies the influence of the random amplitude and phase errors of the antenna array in the actual assembly process and the actual position errors between the subarrays on the electrical performance of the antenna. Based on the planar rectangular antenna array-electromagnetic coupling model, we propose a method of verifying the effect of random errors on the phased array antenna. The simulation result shows that the method could obtain the critical value of the error generated by the antenna subarray during processing and assembly. To reduce the error factor, it is necessary to ensure that the random phase and amplitude error should not exceed 10 ° , 0.5 dB . The error in the X-direction during assembly should be ≤ 0.05 λ , and the error in the Y-direction should be ≤ 0.1 λ . When symmetrical deformation occurs, the maximum deformation should be less than 0.05 λ .