Model-based approaches for decomposing polarimetric backscatter data from boreal forest are discussed in this paper. Several model-based decompositions are analyzed with respect for the most accurate estimation of the volume scattering component. A novel generalized model for description of the volume contribution is proposed when observed backscatter from forest indicates that media does not follow azimuthal symmetry case. The model can be adjusted to the polarimetric synthetic aperture radar (PolSAR) data itself, taking into consideration higher sensitivity of HH against VV backscattering term to the presence of canopy at L-band. The model is general enough to allow a broad range of canopies to be modeled and is shown to comply with several earlier proposed volume scattering mechanism models. It is afterward incorporated in the Freeman-Durden three-component decomposition, yielding an improved modification. The performance of the proposed modification is evaluated using multitemporal ALOS PALSAR data acquired over Kuortane area in central Finland, representing typical mixed boreal forestland. Several decompositions are also benchmarked in order to see how they satisfy physical requirements when decomposing covariance matrix into a weighted sum of individual scattering mechanism contributions. When using experimental data, the proposed decomposition is shown to better satisfy non-negativity constraints for the covariance matrix eigenvalues at each decomposition step with less additional PolSAR data averaging needed. Discussed decompositions are also evaluated for the accuracy of initial stratification based on dominating scattering mechanism using ground reference data.

Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of $3.6$% (86% correlation) and $9.1$% (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.

In this study, four models describing the interferometric coherence of the forest vegetation layer are proposed and compared with the TanDEM-X data. Our focus is on developing tools for hemiboreal forest height estimation from single-pol interferometric SAR measurements, suitable for wide area forest mapping with limited a priori information. The multi-temporal set of 19 TanDEM-X interferometric pairs and the 90th percentile forest height maps are derived from Airborne LiDAR Scanning (ALS), covering an area of 2211 ha of forests over Estonia. Three semi-empirical models along with the Random Volume over Ground (RVoG) model are examined for applicable parameter ranges and model performance under various conditions for over 3000 forest stands. This study shows that all four models performed well in describing the relationship between forest height and interferometric coherence. Use of an advanced model with multiple parameters is not always justified when modeling the volume decorrelation in the boreal and hemiboreal forests. The proposed set of semi-empirical models, show higher robustness compared to a more advanced RVoG model under a range of seasonal and environmental conditions during data acquisition. We also examine the dynamic range of parameters that different models can take and propose optimal conditions for forest stand height inversion for operationally-feasible scenarios.

Scattering phase center (SPC) location in boreal forests was studied in order to assist forest inventory with single- and quad-pol synthetic aperture radar (SAR) interferometry. Airborne X- and L-band interferometric SAR data collected by the DLR E-SAR instrument in southern Finland during the FINSAR campaign was used in the study. A simple Random Volume over Ground (RVoG) model was employed as the theoretical framework for inversion of forest parameters and interpretation of the obtained results. LIDAR measurements of the canopy height and terrain elevation were used as reference and auxiliary data. The RVoG model was found to satisfactorily explain the SPC location inside the canopy in boreal forests. We show that when using X-band, the height of the SPC is typically about 75% of the canopy height, as predicted by the RVoG model; however, the retrieved extinction was found to be rather low. The feasibility of highly accurate tree height inversion using single-polarization X-band interferometry (with RMSE approaching 1.5 m) is demonstrated using a digital terrain model. For this purpose, the traditional polarimetric interferometry SAR technique for phase center retrieval is modified to include a complementary LIDAR measured terrain model. At L-band, the phase center height was determined to be around 50% of the canopy height and even lower, indicating that the ground contribution is significant. Moreover, several simplified inversion approaches for tree height and extinction coefficient retrieval were considered based on several boundary cases of the RVoG model, describing the canopy frequently encountered in boreal forest environments. These analyses allowed developing a combined approach for simultaneous estimation of both forest height and extinction in the boreal zone when an accurate elevation model of the terrain is available.

The ICEYE constellation features the first operational mi-crosatellite based X-band SAR sensors suitable for all-weather day-and-night Earth Observation. In this paper we report on the status of the ICEYE Constellation and describe the characteristics of the first operational imaging modes.