Innovative fiber-laser architecture-based compact wind lidar

Underwater target imaging is important for marine resource exploration, underwater navigation, and related fields. Lidar, with its high angular resolution, excellent depth resolution, and long-distance 3D imaging capabilities, has become an essential tool for target imaging. However, the strong absorption and scattering properties of water, along with the constraints of lidar power consumption and system size, present significant challenges for high-performance lidar systems that are deployable in underwater and even deep-sea environments. To address these challenges, this work proposes and demonstrates a compact, all-fiber underwater imaging lidar. This lidar incorporates highly sensitive single-photon detection technology and features a cylindrical design with a diameter of 0.18 m and a length of 0.68 m. To achieve miniaturization, time-division multiplexing based on fiber arrays is employed, enabling the imaging of small underwater targets using two single-pixel detectors and a two-channel acquisition card. Additionally, an algorithm is introduced to effectively extract and subtract scattering signals from suspended particles in the water column. Tank experiments confirm that the system achieves imaging distances exceeding 10 times the optical attenuation length, and its distance and lateral resolutions are validated using step and stripe targets. With its outstanding performance and broad application potential, this compact lidar system is poised to complement imaging sonar and play a key role in underwater target monitoring and search operations.

We analyze the practical limits of a lidar system based on the use of a laser diode, random binary continuous wave power modulation, and an avalanche photodiode (APD)-based photereceiver, combined with the control and computing power of the digital signal processors (DSP) currently available. The target is to design a compact portable lidar system made all in semiconductor technology, with a low-power demand and an easy configuration of the system, allowing change in some of its features through software. Unlike many prior works, we emphasize the use of APDs instead of photomultiplier tubes to detect the return signal and the application of the system to measure not only hard targets, but also medium-range aerosols and clouds. We have developed an experimental prototype to evaluate the behavior of the system under different environmental conditions. Experimental results provided by the prototype are presented and discussed.

Passive synthetic aperture radar (SAR) using Global Navigation Satellite System (GNSS) signals as the illuminators of opportunity has a relative coarse range resolution due to the narrow bandwidth of the navigation signals and the bi-static acquisition geometry, limiting its application for high-resolution requirement. In this paper, an image formation algorithm for range resolution improvement is investigated. A modified second order differentiation based method is applied on the range compressed signal of reference channel and surveillance channel, improving range resolution and keeping side-lobes at a lower level simultaneously, and the phase of processed signal is preserved by phase multiplication compensation for the following azimuth compression processing. To validate the effectiveness and benefits of the proposed algorithm in terms of range resolution and targets side-lobes, point targets simulation under different situations and real field experiment with strong scatters are conducted and discussed. Compared with the traditional GNSS-based passive SAR imaging algorithm, the results of the proposed method show that the imaging performance can be improved for better range resolution and lower side-lobes, benefitting for better distinguishing nearby targets and recognizing weak targets.

The range resolution of FMCW radar is critical for accurately distinguishing between multiple objects. Higher range resolution allows for better object separation and more precise location determination. While increasing the bandwidth can improve range resolution, it also raises costs and may be subject to regulatory constraints on the available frequency spectrum. This paper proposes an approach to enhance range resolution by increasing the effective bandwidth through signal processing, specifically by introducing the Estimated Signal Padding (ESP) method. ESP extends the bandwidth by lengthening the signal in the time domain, creating a synthesized signal for each target. The proposed algorithm can improve range resolution by a factor of at least 2.25. Unlike existing methods such as Zero Padding and Neural Network Padding, the proposed algorithm can distinguish targets of varying sizes rather than only targets of the same size. The performance of the algorithm has been validated through MATLAB simulations and FMCW radar experiments.

Traditional laser scanners for 3D distance measurement involve expensive, heavy, (potentially) slow rotating mirrors for light deflection of the scanning TOF (time of flight) distance measurement, not suitable for compact, robust and highly portable LIDAR system. On the other hand MEMS scanners are limited to small apertures not suitable for a precise TOF measurement. To overcome this problem Fraunhofer IPMS presents a large aperture 1D-MEMS scanner array especially designed for LIDAR applications. It is composed of 2 × 7 silicon mirror elements each having an identical design with comparatively large aperture of 2.51 × 9.51mm2 and ±30° optical scan range. All mirrors are driven electrostatically resonant with identical frequency close to design frequency of 250 Hz. By driving control all single scanner elements are synchronized to identical phase and amplitude in respect to a master scanner. This results in a large effective scanner aperture of 334 mm2 for the receiver optics and a filling factor of 80 %. To guarantee the synchronized operation the paper discusses in detail the scanner design to enable a sufficiently large frequency bandwidth of all scanner elements to the compensate frequency tolerances caused by fabrication and packaging. In comparison to LIDAR systems with conventional scanner components, the large aperture 1D-MEMS scanner array enables 3D-LIDAR systems to become significantly smaller, more robust and (potentially) less expensive, also higher scan rates can be realized without additional efforts (e.g. no air bearings are needed).

Investigations of lidar-assisted control to optimize the energy yield and to reduce loads of wind turbines have increased significantly in recent years. For this kind of control, it is crucial to know the correlation between the rotor effective wind speed and the wind preview provided by a nacelle- or spinner-based lidar system. If on the one hand, the assumed correlation is overestimated, then the uncorrelated frequencies of the preview will cause unnecessary control action, inducing undesired loads. On the other hand, the benefits of the lidar-assisted controller will not be fully exhausted, if correlated frequencies are filtered out. To avoid these miscalculations, this work presents a method to model the correlation between lidar systems and wind turbines using Kaimal wind spectra. The derived model accounts for different measurement configurations and spatial averaging of the lidar system, different rotor sizes, and wind evolution. The method is compared to real measurement data with promising results. In addition, examples depict how this model can be used to design an optimal controller and how the configuration of a lidar system is optimized for a given turbine to improve the correlation.

In order to achieve good range resolution and accuracy on frequency-modulated continuous-wave (FMCW) radars, highly linear chirps are necessary. Voltage-controlled oscillators (V COs) present nonlinearities in their tuning curve. Then, once VCOs are a fundamental building block in many continuous-wave radar systems, these nonlinearities translate into negative effects in terms of range resolution performance. A common approach to generating linear tuning curves is to connect the system VCO to a phase-locked loop (PLL). Although, PLLs increase the system complexity and cost. This work presents a way to improve the range resolution in a portable and low-cost C-band FMCW radar system. The radar VCO is driven by a microcontroller that applies a customized waveform developed to compensate for the nonlinear behavior to achieve such results.

In the paper one of high range resolution methods – Aperture Sampling – was analysed. Unlike MUSIC based techniques it proved to be very efficient in terms of achieving unambiguous synthetic range profile for ultra-wideband stepped frequency continuous wave radar. Assuming that minimal distance required to separate two targets in depth (distance) corresponds to -3 dB width of received echo, AS provided a 30,8 % improvement in range resolution in analysed scenario, when compared to results of applying IFFT. Output data is far superior in terms of both improved range resolution and reduced side lobe level than used typically in this area Inverse Fourier Transform. Furthermore it does not require prior knowledge or an estimate of number of targets to be detected in a given scan.

In time-of-flight (TOF) range image sensors using periodical pulsed light, there is a trade-off between the maximum range and range resolution. This paper proposes a technique for improving range resolution of the TOF range image sensor using range shifting. In the TOF range image sensor with ambient light draining structure, the amount of delay of short light pulse is changed depending on the measurement range. This technique improves the range resolution without reducing the measurement range. The use of the small duty-ratio pulse also leads to reducing the effect of ambient light. The range-shift technique is tested with an implemented TOF range image sensor and it is found that the range resolution is improved to 2 cm using 10 ns light pulse and 7 zones for the measurement range of 0.5 m to 4 m.

A frequent problem in radar meteorology is that the range resolution available is insufficient to investigate small scale atmospheric features such as thin layers. The problem is particularly acute for MST (mesosphere, stratosphere, troposhere) VHF radars which rarely have range resolutions better than 150 metres, however thin layers in the lower atmosphere are known to have vertical scale sizes less than this. Such layers may contain turbulence and/or have step-function changes in the radar refractive index. One approach to improving radar resolution is to switch rapidly between two closely-spaced frequencies in a technique known as frequency domain interferometry (FDI). This requires hardware changes to the system and can lead to some ambiguity in the results, but has nonetheless been successfully applied in a number of MST radar studies. The authors present a new approach that requires no hardware changes and can be applied to previously recorded data retrospectively, provided the system characteristics are known. The technique, known as best linear estimate super-resolution, improves range resolution through the use of 'prior knowledge' of the system impulse response, the scattering model and some of the target characteristics.

<p>Atmospheric motion and turbulence are essential parameters for weather and topics related to air quality. Therefore, wind profile measurements play an important role in atmospheric research and meteorology. One source of wind profile data are Doppler wind lidars, which are laser-based remote sensing instruments that measure wind speed and wind direction up to a few hundred meters or even a few kilometers. Commercial wind lidars use the laser wavelength of 1.5 µm and therefore backscatter is mainly from aerosols while clear air backscatter is minimal, limiting the range to the boundary layer typically.</p><p>We have carried out a two-year intercomparison of the ZephIR 300M (ZX Lidars) short-range wind lidar and tall mast wind measurements at Cabauw [1]. We have focused on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213m tall meteorological mast. We have found an overall availability of quality-controlled wind lidar data of 97% to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm/h or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m/s with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. This instrument is being deployed within North Sea wind farms.</p><p>Recently, a scanning long-range wind lidar Windcube 200S (Leosphere/Vaisala) has been installed at Cabauw, as part of the Ruisdael Observatory program [2]. The scanning Doppler wind lidars will provide detailed measurements of the wind field, aerosols and clouds around the Cabauw site, in coordination with other instruments, such as the cloud radar.</p><p>[1] Knoop, S., Bosveld, F. C., de Haij, M. J., and Apituley, A.: A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw, Atmos. Meas. Tech., 14, 2219–2235, 2021</p><p>[2] https://ruisdael-observatory.nl/</p>

In this work the spectra based model of the correlation between lidar systems and wind turbines is extended from rotor-effective wind speed only, to rotor-effective wind speed and linear horizontal and vertical shear components. This is achieved by the incorporation of a model based wind field reconstruction method solving a set of linear equations with the least-squares method. The model allows to optimize a lidar system’s measurement configuration for a specific wind turbine a-priori by means of direct and fast spectra calculations. Furthermore, it allows to assess the filter parameters to be expected and needed for the application of lidar-assisted control. By extending the model to rotor-effective linear shears, the results can be used for lidar-assisted individual pitch control.

The requirement of high range resolution results in impractical collection of every returned laser pulse due to the limited response speed of imaging detectors. This paper proposes a phase coded sequence acquisition method for signal preprocessing. The system employs an m-sequence with N bits for demonstration with the detector controlled to accumulate N+1 bits of the echo signals to deduce one single returned laser pulse. An indoor experiment achieved 2 μs resolution with the sampling period of 28 μs by employing a 15-bit m-sequence. This method shows the potential to improve the detection capabilities of narrow laser pulses with the detectors at a low frame rate, especially for the imaging lidar systems. Meanwhile, the lidar system is able to improve the range resolution with available detectors of restricted performance.

3D gated range-intensity correlation imaging (GRICI) can reconstruct a 3D scene with high range resolution in real time. However, in the applications of underwater range-gated imaging, targets with low reflectivity or at a far distance typically have a low signal-to-noise ratio (SNR), especially in turbid water. Usually, a global threshold is set to suppress noise in gated images, which easily results in data holes in the degraded depth map reconstructed by 3D GRICI. To solve the problem, we have proposed a binning-based local-threshold filtering (BLF) algorithm to fill depth data holes. Firstly, raw gated images are added to obtain a sum image, and global threshold filtering and pixel binning for the sum image are used to obtain a reference image. Secondly, hole pixels can be registered according to the reference image. Finally, a smaller local threshold is reset for the hole pixels, and then a repaired depth map is given by 3D GRICI. The experimental results have shown that the proposed method can effectively fill depth data holes and the peak signal-to-noise ratio of the repaired depth map is increased from 10.23 dB to 22.45 dB by suppressing water noise with the improved range resolution from 6.25 mm to 4.12 mm. In addition, the 3D depth of viewing is enlarged, and the limit detection distance is increased by 21% in experiment. The research can promote the practical applications of 3D GRICI.

Wind energy research relies on remote sensing technologies like dual-Doppler (DD) lidar and radar, or space-born SAR data to estimate complex meteorological conditions and the flow field around wind farms. Offshore measurement campaigns over the last decade accentuate the potential of DD wind radar technology for wind energy application. Onshore, promising results were also reported as part of the American WAKE ExperimeNt (AWAKEN).The main drawback of wind radar technology is that further characterisation of radar measurement accuracy is required for industry implementation. We investigate X-band wind radar measurement accuracy in a comparison study, using meteorological mast data and wind lidars from an onshore measurement campaign. Despite their cost, meteorological masts provide very accurate point measurements over specific heights, and are the preferred reference for wind validation. Wind lidars are a proven alternative, as demonstrated in several offshore campaigns. Like for lidars, radar's measurement principle is based on the Doppler effect, and both devices allow for wind field estimates. Yet, radars can scan over larger distances at a much higher sampling rate, with increased resolution along the beam due to the use of a compressed pulse. However, unlike pulsed lidars that emit collimated beams, the radar beam expands with distance, which arguably adds uncertainty to the measurements at far ranges. A dual-Doppler lidar-radar set-up is used with the remote sensing devices collocated in space, but measuring a-synchronously. We conduct the analysis on wind component basis (u, v) and wind speed and direction, focusing on inflow in front of a large wind turbine (OPUS 1) at the onshore Wivaldi Test Site in Northern Germany, as part of the radar Krummendeich Campaign. Lidars and radars are deployed approximately 3 km to 4 km away from the collocated lidar - meteorological mast - radar measurements. Although the influence of increased probe volume averaging, due to beam expansion, in distance is unclear due to campaign set-up, the results presented set a ground base for further use of long range wind lidars as validation for upcoming radar measurement campaigns.