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Spotlight Synthetic Aperture Radar Signal Processing Algorithms

The new level of precision and global coverage provided by satellite altimetry is rapidly advancing studies of ocean circulation. It allows for new insights into marine geodesy, ice sheet movements, plate tectonics, and for the first time provides high-resolution bathymetry for previously unmapped regions of our watery planet and crucial information on the large-scale ocean features on intra-season to interannual time scales. Satellite Altimetry and Earth Sciences has integrated the expertise of the leading international researchers to demonstrate the techniques, missions, and accuracy of satellite altimetry, including altimeter measurements, orbit determination, and ocean circulation models. Satellite altimetry is helping to advance studies of ocean circulation, tides, sea level, surface waves and allowing new insights into marine geodesy. Satellite Altimetry and Earth Sciences provides high resolution bathymetry for previously unmapped regions of our watery planet. Satellite Altimetry and Earth Sciences is for a very broad spectrum of academics, graduate students, and researchers in geophysics, oceanography, and the space and earth sciences. International agencies that fund satellite-based research will also appreciate the handy reference on the applications of satellite altimetry.

Satellite altimetry and Earth sciences :a handbook of techniques and applications

Automated individual tree crown detection and delineation (ITCD) using remotely sensed data plays an increasingly significant role in efficiently, accurately, and completely monitoring forests. This paper reviews trends in ITCD research from 1990–2015 from several perspectives—data/forest type, method applied, accuracy assessment and research objective—with a focus on studies using LiDAR data. This review shows that active sources are becoming more prominent in ITCD studies. Studies using active data—LiDAR in particular—accounted for 80% of the total increase over the entire time period, those using passive data or fusion of passive and active data comprised relatively small proportions of the total increase (8% and 12%, respectively). Additionally, ITCD research has moved from incremental adaptations of algorithms developed for passive data sources to innovative approaches that take advantage of the novel characteristics of active datasets like LiDAR. These improvements make it possible to explore more complex forest conditions (e.g., closed hardwood forests, suburban/urban forests) rather than a single forest type although most published ITCD studies still focused on closed softwood (41%) or mixed forest (22%). Approximately one-third of studies applied individual tree level (30%) assessment, with only a quarter reporting more comprehensive multi-level assessment (23%). Almost one-third of studies (32%) that concentrated on forest parameter estimation based on ITCD results had no ITCD-specific evaluation. Comparison of methods continues to be complicated by both choice of reference data and assessment metric; it is imperative to establish a standardized two-level assessment framework to evaluate and compare ITCD algorithms in order to provide specific recommendations about suitable applications of particular algorithms. However, the evolution of active remotely sensed data and novel platforms implies that automated ITCD will continue to be a promising technology and an attractive research topic for both the forestry and remote sensing communities.

https://www.mdpi.com/2072-4292/8/4/333/pdf

Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data

http://oa.upm.es/2128/2/INVE_MEM_2008_52781.pdf

Fire models and methods to map fuel types: The role of remote sensing

Under assumptions common in radar altimetry, the mean backscattered return power for a short-pulse radar and near-normal-incidence scattering from a rough ocean surface is given by the convolution of several terms. For a nearly Gaussian transmitted pulse shape scattered from a nearly Gaussian distributed sea surface, a small-argument series expansion of one of the terms within the convolution leads to a several-term power series expansion for the mean return waveform. Specific expressions are given for the first four terms. These results, which require much less computer time than would the otherwise necessary numerical convolution, are useful for data analysis from current or past radar altimeters and for design studies of future systems. Several representative results are presented for an idealized SEASAT radar altimeter.

Radar altimeter mean return wave forms from near-normal-incidence ocean surface scattering

This paper presents a multi-input multi-output (MIMO) radar with simultaneously transmitted orthogonal waveforms. The radar operates in W-band, 93.5–94.5 GHz, with frequency-modulated continuous wave (FMCW) signals. The radar is designed to be capable of simultaneous transmission rather than switching transmit channels. A suitable orthogonal waveform transmission method for the FMCW radar is selected and reflected in the transceiver design. The radar consists of a transceiver, antennas, and a signal processor. The design and specifications of each module are described in detail. The transceiver consists of two transmitting channels and two receiving channels. The transmitter is designed to have high transmit power aiming at the detection and imaging of objects with small radar cross section, up to 100–150-m range. A compact horn antenna and two-channel analog-to-digital converter with a high sampling rate are designed and fabricated. The performance of each module is measured and evaluated. The performance of the radar is tested through experiments. The MIMO capability of the radar was verified through the acquisition of the range profiles with respect to four distinct signal paths by distinguishing the simultaneously transmitted orthogonal signals. The experimental results verified that the specification of the radar system is feasible for high-resolution imaging applications.

W-Band MIMO FMCW Radar System With Simultaneous Transmission of Orthogonal Waveforms for High-Resolution Imaging

A simple statistical extension at the individual tree level for an earlier-developed very high frequency forest backscatter model is proposed. This extended model treats trunk volumes as random quantities. A concept of random forest reflection coefficient is also introduced to characterize radar returns from individual trees. Based on the extended model, a set of algorithms for estimating the mean trunk (stem) volume from synthetic aperture radar data at the individual tree level is developed assuming that the areal tree density is known. The algorithms are specified for different scenarios related to a priori information on parameters of statistical distributions for the trunk volume and fluctuations of the forest reflection coefficient. An approximate lower bound on the standard deviation in the unbiased estimation of the mean trunk (stem) volume is proposed. This bound can be readily obtained by means of computer simulation for any specified statistical distribution for the trunk volume and fluctuations of the forest reflection coefficient. Performance analysis for the proposed algorithms is numerically performed by means of Monte Carlo simulation for a variety of scenarios. This analysis has shown that the algorithms provide nearly unbiased and efficient estimates, and the proposed lower bound is a very accurate approximation. The results of the study have demonstrated that the approach and methods developed in this paper suggest promising solutions in accurate forest parameter retrieval.

Model-Associated Forest Parameter Retrieval Using VHF SAR Data at the Individual Tree Level

This paper discusses radar-based technologies that provide drivers with information about road curves under conditions in which optical sensors are unable to perform. The development of a task capable of estimating road curves has become a popular challenge since the commencement of the active development of advanced driver assistance systems and autonomous vehicles. Although the hardware implementation of a road curvature measurement system may have many variations, including cameras, we consider microwave sensors to be a reasonable alternative that offers many benefits. Road curvature measurement requires fast acquisition of the necessary data from a moving vehicle followed by efficient postprocessing of the data to identify a sufficient number of reliable featured points in the local environment. These points would enable a hypothesis about the dimensions and shape of the probable road geometry to be built. Different studies attempted to solve this problem using specialized equipment and custom-built algorithms. Our solution is to use a commercially available radar and some preprocessing and postprocessing algorithms for data conditioning and analysis to obtain reliable results in both day- and night-time environments and under various weather conditions in a relatively short time using a simplified approach based on circle-fitting algorithms. We confirmed the effectiveness of the proposed approach by conducting multiple road experiments with a commercially available microwave sensor. Considering that the road infrastructure is currently not optimized for road curvature measurements, the results we obtained with our proposed method (within 10%–17% of those on the actual map) are acceptable.

Application of $W$ -Band FMCW Radar for Road Curvature Estimation in Poor Visibility Conditions

A new method of sidelobe level (SLL) reduction for a substrate integrated waveguide (SIW) slot array antenna is presented. In this method, amplitude distribution is assigned to the slots by tapering the SIW width. The SIW with tapered width can be efficiently manufactured by varying the position of the side-wall vias. In this letter, the new method is verified on a 12-element SIW slot array antenna operating at 94 GHz to achieve SLL around –30 dB. The antenna design procedure as well as simulation and measurement results are presented.

A Sidelobe Level Reduction Method for mm-Wave Substrate Integrated Waveguide Slot Array Antenna

Radar signals are synthesized having a region of zero autocorrelation sidelobes with a relative width of $1/3\leq \varepsilon in the vicinity of the central peak of an aperiodic autocorrelation function These signals represent a train of two binary phase-coded pulses encoded by pair of complementary sequences of length $N=2^k$ , with an integer $k\geq 2$  The correlation characteristics of the synthesized signal are analyzed A compression algorithm for these signals, multichannel with respect to the Doppler frequency, is considered It includes a combined algorithm for fast Walsh and Fourier transforms

Min-Ho Ka

Papers

W-Band MIMO FMCW Radar System With Simultaneous Transmission of Orthogonal Waveforms for High-Resolution Imaging

Model-Associated Forest Parameter Retrieval Using VHF SAR Data at the Individual Tree Level

Application of $W$ -Band FMCW Radar for Road Curvature Estimation in Poor Visibility Conditions

A Sidelobe Level Reduction Method for mm-Wave Substrate Integrated Waveguide Slot Array Antenna

Radar Signals With ZACZ Based on Pairs of D-Code Sequences and Their Compression Algorithm