An FMCW radar system for short range surface contour mapping

The surface of a fluidized bed combustor may be indicative of problems, such as agglomeration, occurring within the bed material. The imaging system described in this dissertation has the potential of becoming a diagnostic tool to serve this purpose. The goal of this project was to design and evaluate a radar-based, phased-array system for capturing the surface contours of static surfaces located short distances (approximately 8 ft.) from the antenna array;The energy source for the contour mapping system was a frequency modulated, continuous wave (FMCW) radar. Since the frequency of a demodulated FCMW signal is proportional to the distance to the target, the dominant frequency component of the output from the beamforming algorithm is an estimate of the distance to the surface;This dissertation describes the equipment arrangement, the noise removal methods, and the delay and sum beamforming algorithm. In addition, results for several different surface types and structures are presented and discussed. Since it is shown that this prototype system has limitations, recommendations for future modifications are also suggested

An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar

Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica

Antarctic sea ice and its snow cover are integral components of the global climate system, yet many aspects of their vertical dimensions are poorly understood, making their representation in global climate models poor. Remote sensing is the key to monitoring the dynamic nature of sea ice and its snow cover. Reliable and accurate snow thickness data are currently a highly sought after data product. Remotely sensed snow thickness measurements can provide an indication of precipitation levels, predicted to increase with effects of climate change in the polar regions. Airborne techniques provide a means for regional-scale estimation of snow depth and distribution. Accurate regional-scale snow thickness data will also facilitate an increase in the accuracy of sea ice thickness retrieval from satellite altimeter freeboard estimates. The airborne data sets are easier to validate with in situ measurements and are better suited to validating satellite algorithms when compared with in situ techniques. This is primarily due to two factors: better chance of getting coincident in situ and airborne data sets and the tractability of comparison between an in situ data set and the airborne data set averaged over the footprint of the antennas. A 28-GHz frequency modulated continuous wave (FMCW) radar loaned by the Center for Remote Sensing of Ice Sheets to the Australian Antarctic Division is used to measure snow thickness over sea ice in East Antarctica. Provided with the radar design parameters, the expected performance parameters of the radar are summarized. The necessary conditions for unambiguous identification of the airsnow and snowice layers for the radar are presented. Roughnesses of the snow and ice surfaces are found to be dominant determinants in the effectiveness of layer identification for this radar. Finally, this paper presents the first in situ validated snow thickness estimates over sea ice in Antarctica derived from an FMCW radar on a helicopterborne platform

A system-on-chip microwave photonic processor solves dynamic RF interference in real time with picosecond latency

Radio-frequency interference is a growing concern as wireless technology advances, with potentially life-threatening consequences like interference between radar altimeters and 5G cellular networks. Mobile transceivers mix signals with varying ratios over time, posing challenges for conventional digital signal processing (DSP) due to its high latency. These challenges will worsen as future wireless technologies adopt higher carrier frequencies and data rates. However, conventional DSPs, already on the brink of their clock frequency limit, are expected to offer only marginal speed advancements. This paper introduces a photonic processor to address dynamic interference through blind source separation (BSS). Our system-on-chip processor employs a fully integrated photonic signal pathway in the analogue domain, enabling rapid demixing of received mixtures and recovering the signal-of-interest in under 15 picoseconds. This reduction in latency surpasses electronic counterparts by more than three orders of magnitude. To complement the photonic processor, electronic peripherals based on field-programmable gate array (FPGA) assess the effectiveness of demixing and continuously update demixing weights at a rate of up to 305 Hz. This compact setup features precise dithering weight control, impedance-controlled circuit board and optical fibre packaging, suitable for handheld and mobile scenarios. We experimentally demonstrate the processor's ability to suppress transmission errors and maintain signal-to-noise ratios in two scenarios, radar altimeters and mobile communications. This work pioneers the real-time adaptability of integrated silicon photonics, enabling online learning and weight adjustments, and showcasing practical operational applications for photonic processing

Frequency-modulated continuous-wave synthetic-aperture radar: improvements in signal processing

With the advance of solid state devices, frequency-modulated continuous-wave (FMCW) designs have recently been used in synthetic-aperture radar (SAR) to decrease cost, size, weight and power consumption, making it deployable on smaller mobile plat-forms, including small (< 25 kg) unmanned aerial vehicle(s) (UAV). To foster its mobile uses, several SAR capabilities were studied: moving target indication (MTI) for increased situational awareness, bistatic operation, e.g. in UAV formation flights, for increased range, and signal processing algorithms for faster real-time performance. Most off-the-shelf SAR systems for small mobile platforms are commercial proprie-tary and/or military (ITAR, International Trades in Arms Regulations) restricted. As such, it necessitated the design and build of a prototype FMCW SAR system at the early stage to serve as a research tool. This enabled unrestricted hardware and software modifica-tions and experimentation. A model to analyze the triangularly modulated (TM) linear frequency modulated (LFM) waveform as one signal was established and used to develop a MTI algorithm which is effective for slow moving targets detection. Experimental field data collected by the prototyped FMCW SAR was then used to validate and demonstrate the effectiveness of the proposed MTI method. A bistatic FMCW SAR model was next introduced: Bistatic configuration is a poten-tial technique to overcome the power leakage problem in monostatic FMCW SAR. By mounting the transmitter and receiver on spatially separate mobile (UAV) platforms in formation deployment, the operation range of a bistatic FMCW SAR can be significantly improved. The proposed approximation algorithm established a signal model for bistatic FMCW SAR by using the Fresnel approximation. This model allows the existing signal processing algorithms to be used in bistatic FMCW SAR image generation without sig-nificant modification simplifying bistatic FMCW SAR signal processing. The proposed range migration algorithm is a versatile and efficient FMCW SAR sig-nal processing algorithm which requires less memory and computational load than the traditional RMA. This imaging algorithm can be employed for real-time image genera-tion by the FMCW SAR system on mobile platforms. Simulation results verified the pro-posed spectral model and experimental data demonstrated the effectiveness of the modi-fied RMA

AUTONOMOUS SURFACE DETECTION AND TRACKING FOR FMCW SNOW RADAR USING FIELD PROGRAMMABLE GATE ARRAYS

Sea Ice in Polar Regions is typically covered with a layer of snow. The thermal insulation properties and high albedo of the snow cover insulates the sea ice beneath it, maintaining low temperatures and limiting ice melt, and thus affecting sea ice thickness and growth rates. Remote sensing of snow cover thickness plays a major role in understanding the mass balance of sea ice, inter-annual variability of snow depth, and other factors which directly impact climate change. Researchers at the Center for Remote Sensing of Ice Sheets (CReSIS) at University of Kansas have developed an ultra-wide band FMCW Snow Radar used to measure snow thickness and map internal layers of polar firn from low and high-altitude. This system has shown outstanding performance, but it has some limitations in terms of operational altitude and relies on the operator to make adjustments during surveys to capture radar echoes if the altitude changes significantly. In this thesis, an automated onboard real-time surface tracker for the snow radar is presented to detect snow surface elevation from the aircraft and track changes in the surface elevation. A common technique for an FMCW radar to have a long-range (high-altitude) capability relies on the system’s ability to delay the reference chirp signal used for de-chirping to maintain a relatively constant beat frequency. Currently, the radar uses an analog filter bank to condition the received IF signal over discrete altitude ranges and store the spectral power in each band utilizing different Nyquist zones. During airborne missions in Polar Regions with the radar, the operator has to manually switch the filter banks whenever there is a significant change in aircraft elevation. The work done in this thesis aims at eliminating the manual switching operation and providing the radar with surface detection, chirp delay, and a constant beat frequency feedback loop to enhance its long-range capability and ensure autonomous operation

Precise inland surface altimetry (PISA) with nadir specular echoes from Sentinel-3: Algorithm and performance assessment

Abstract In the recent years satellite radar altimetry has evolved from pulse-limited low resolution mode (LRM) to a synthetic aperture radar (SAR) high resolution mode. The SAR mode focusses and coherently sums all radar return echoes within the 2-s time window the target surface area is in the antenna beam. In principle the SAR processing improves along-track resolution. Land contamination has been a major concern for inland waters altimetry and SAR can reduce land interference. This paper shows that the physics of specular echoes from smooth inland waters leads to a very different approach which we call precise inland surface altimetry (PISA). PISA uses only echoes within the specular "flash" period, which is approximately the time the satellite nadir crosses over the water body. The processing is four orders of magnitude less than SAR. Land interference is negligible because specular water echoes are usually >50 dB greater than land. Sentinel-3 SRAL dataset on the salar de Uyuni (Bolivia) is used to evaluate PISA ranging precision. During inundation (wet months), echoes are at the theoretical maximum radar cross section (RCS), σ = 129 dBsm, and ranging precision is ~1 mm. In dry months the echoes are quasi-specular, with σ = 70–100 dBsm, and ranging precision is ~1 cm. The precision assessment is made with variate-differences, with pass-to-pass repeatability, and by comparison with GPS measurements. In addition to the salar de Uyuni analysis we gathered σ statistics on five millions Sentinel-3 SRAL Ku-band altimeter bursts (one burst = 64 contiguous echoes) from 52 passes of Sentinel-3A track 167 over South America. We illustrate specular and quasi-specular waters on lakes, a river, and a fjord. Ranging precision is similar to Uyuni, in the 1 mm-1 cm range. Water surface slopes of 1–3 cm/km are detected. We propose a simple rule-set to distinguish specular waveforms (σ >100 dBsm, sidelobes (with Hamming window) of −37 dB or lower) and quasi-specular (σ >70 dBsm, sidelobes lower than −20 dB), and non-specular (sidelobes> − 20 dB). PISA is appropriate to specular and quasi-specular echoes

In search for the best wavelet for denoising low SNR RF Signal for FMCW Radar Altimeter

This research project / thesis proposes the best wavelet for Denoising under low Signal to Noise Ratio (SNR) conditions and Discrete Wavelet Transform Architecture based design for RF signal denoising, targeting the real time applications like FMCW (Frequency Modulated Continuous Wave) Radar Altimeter used in Anti-Radiation Missiles, Smart Bombs, Fighter aircrafts, Helicopters etc., and other Defense and RF carrier based applications like Cellular communication. DWT (Discrete Wavelet Transform) & IDWT(Inverse DWT) Architecture Models designed in MATLAB for the wavelets under study like dmey, coif1, sym2, & debouches db1, db2, db3, db4, db6. The reconstructed signal results after denoising are compared in various aspects. The results show that db3 is the best wavelet for denoising application point of view. Finally the db3 based architecture design implemented in VHDL(VHSIC Hardware Description Language) and the simulation results compared, synthesis has been done using Xilinx ISE Design suite targeting an FPGA. This project involves study and implementation of De-noising algorithms using Discrete Wavelet Transform. In a system the signal to noise ratio (SNR) is important for reliable information retrieval. Analysis of signals with poor SNR may lead to wrong interpretation of results. Conventional techniques like filtering in time domain and frequency domain has its own limitations in estimating and characterizing noise. Wavelet transforms is a very useful tool in the analysis of non-stationary signals. Wavelet transform has been used in signal processing fields such as de noising or data compression. This method consists of decomposing the data recursively into a sum of details and approximations at different levels of resolution. The details represent the high frequency components while the approximations represent the low frequency components of the signal