Raphaël Rouveure

Impact of Soil Structure on Microwave Volume Scattering Evaluated by a Two-Dimensional Numerical Model

Soil volumetric structure is an important parameter for tillage operation. The aim of this paper is to assess whether volume characteristics can be inferred from radar measurements. A 2-D numerical model (the 2DSCAT model) was developed based on a numerical solver using a time-domain finite-element method to solve Maxwells equations. Perfectly matched layers were implemented as well as a near- to far-field transformation. A focused incident beam was generated by adapting the boundary conditions. To represent the soil structure, a simulator was developed describing the soil as biphasic media (fine earth and clods). Clods were represented by randomly deformed ellipses, with randomly determined dimensions, locations, and orientations. The model performed successfully, as evaluated against exact analytical solutions available for an infinite perfectly conducting cylinder and the reflection of flat semi-infinite media. The model was then evaluated against measurements made by an X-band FM continuous-wave radar on a box filled with dry clods of different sizes. The effect of the clod size on the backscattering power was very well reproduced, showing the potential of using a 2-D numerical model to understand microwave-backscattering patterns from cloddy soils. Analysis of the volume scattering shows that this phenomenon can be mostly hidden in the scatter diagram by surface scattering when the latter occurred. However, the volume scattering gives a stronger residual signal in time because of propagation through the medium. Thus, time studies of the scattering signal provide further information about volume heterogeneities.

Toward 3D Reconstruction of Outdoor Scenes Using an MMW Radar and a Monocular Vision Sensor

In this paper, we introduce a geometric method for 3D reconstruction of the exterior environment using a panoramic microwave radar and a camera. We rely on the complementarity of these two sensors considering the robustness to the environmental conditions and depth detection ability of the radar, on the one hand, and the high spatial resolution of a vision sensor, on the other. Firstly, geometric modeling of each sensor and of the entire system is presented. Secondly, we address the global calibration problem, which consists of finding the exact transformation between the sensors’ coordinate systems. Two implementation methods are proposed and compared, based on the optimization of a non-linear criterion obtained from a set of radar-to-image target correspondences. Unlike existing methods, no special configuration of the 3D points is required for calibration. This makes the methods flexible and easy to use by a non-expert operator. Finally, we present a very simple, yet robust 3D reconstruction method based on the sensors’ geometry. This method enables one to reconstruct observed features in 3D using one acquisition (static sensor), which is not always met in the state of the art for outdoor scene reconstruction. The proposed methods have been validated with synthetic and real data.

A mobile ground-based radar sensor for detection and tracking of moving objects

The detection and tracking of moving objects (DATMO) in an outdoor environment from a mobile robot are difficult tasks because of the wide variety of dynamic objects. A reliable discrimination of mobile and static detections without any prior knowledge is often conditioned by a good position estimation obtained using Global Positionning System/Differential Global Positioning System (GPS/DGPS), proprioceptive sensors, inertial sensors or even the use of Simultaneous Localization and Mapping (SLAM) algorithms. In this article a solution of the DATMO problem is presented to perform this task using only a microwave radar sensor. Indeed, this sensor provides images of the environment from which Doppler information can be extracted and interpreted in order to obtain not only velocities of detected objects but also the robots own velocity.

Radar Imager for Perception and Mapping in Outdoor Environments

Perception remains a challenge in outdoor environments. Overcoming the limitations of vision-based sensors, microwave radar presents considerable potential. Such a sensor so-called K2Pi has been designed for environment mapping. In order to build radar maps, an algorithm named R-SLAM has been developed. The global radar map is constructed through a data merging process, using map matching of successive radar image sequences. An occupancy grid approach is used to describe the environment. First results obtained in urban and natural environments are presented, which show the ability of the microwave radar to deal with extended environments.

A multi-layer feed-forward perceptron for microwave signals processing

This paper investigates the processing of radar signals using artificial neural networks. Today, the use of FMCW radar is considered to control the agricultural implements working depth, in order to overcome the limitations of sensors based on optical or ultrasound devices towards agricultural environment (dust, rain, etc.). The objective is to determine the radar-target distance R with a direct identification of the discrete-time radar signal S/sub b/[n]. The neural network structure in a multi-layer feed-forward perceptron. Using simulation studies, we illustrate the capability of this neural network in determining the relation between R and S/sub b/. The first training strategy uses non-disturbed input data, but this solution leads to an important overfitting when noise is added to the input signals. The second strategy reduces this sensitivity by carrying out the training phase with noisy input data. A comparison of accuracy and computing times is achieved between neural network and spectral analysis (FFT).

A microwave sensor for agricultural implements

For soil preparation, the concept of precision agriculture requires real time measurements of soil characteristics and cultivator behavior. The microwave sensor presented in this paper overcomes the limitations of sensors based on optical or ultrasound devices towards agricultural environment (dust, rain, etc.). The sensor uses the principle of frequency-modulated continuous wave (FM-CW) radar, low cost technology well intended for short range applications. First laboratory results of two major applications are presented. The first one is the distance measurement applied to the control of working depth. Soil-implement distances are computed with the measurement of a beat frequency: a maximum positioning error of /spl plusmn/5 mm is obtained for distances between 0.7 and 1 m. The second one is the evaluation of soil roughness in order to control seedbed quality. The backscattered coefficient, measured at normal incidence with samples of dry soil, is correlated with the rms height.

PELICAN: Panoramic millimeter-wave radar for perception in mobile robotics applications. Part 1: Principles of FMCW radar and of 2D image construction

Robust environmental perception is a crucial parameter for the development of autonomous ground vehicle applications, especially in the field of agricultural robotics which is one of the priorities for the Horizon 2020 robotics funding (EU funding program for research and innovation). Because of uncontrolled and changing environmental conditions in outdoor and natural environments, data from optical sensors classically used in mobile robotics can be compromised and unusable. In such situations, millimeterwave radar can provide an alternative and complementary solution for perception tasks. The aim of this paper is to present the PELICAN radar, a millimeter-wave radar specifically designed for mobile robotics applications, including obstacle detection, mapping and situational awareness in general. In this first of a two-part paper, the choice of a frequency-modulated continuous-wave radar is explained and the theoretical elements of this solution are detailed. PELICAN radar is using a rotating fan-beam antenna, and the construction of 2D representations of the surrounding environments with radar data is described through simulation results. The second part of the paper will be devoted for a detailed description of PELICAN radar, as well as experimental results.

Using Proximal Sensors to Continuously Monitor Agricultural Soil Physical Conditions for Tillage Management

Homogeneity of crop establishment, which directly depends on physical conditions within the seedbed, is very important for crop yield. We did a field experiment to test the abilities of various sensors to characterise seedbed physical conditions and the possibility of continuously modifying the intensity of soil tillage with the objective of producing a uniform seedbed. The experiment was done on a silt soil with 19% clay and 74% silt in northern France. We created two initial soil structures (with and without clods >10 cm) and controlled water content (field capacity or less). A special cultivator was developed with a continuous-output GPS and a microwave ground-based radar sensor; it also carried a laser profile meter for soil surface characterisation, a capacitance probe for monitoring soil water content, and a load cell for measuring soil mechanical resistance. Each sensor was able to detect differences in soil physical conditions at the field scale. Because of the simultaneous effect of soil water content and soil structure on the geophysical parameters obtained with the sensors, it was not possible to obtain a continuous characterisation of the soil’s bulk density, water content, clod-size distribution, or surface roughness (although the use of two radar angles of incidence might allow better assessment of soil surface roughness). For tillage control, seedbed conditions depended on initial soil conditions (water content and degree of compaction) and soil tillage tool characteristics (working depth and speed of rotation). Working depth and speed of rotation had opposite effects on the size of clods at the seedbed surface; within the seedbed, they could reduce initial soil variability. Seeding rate could be controlled by the same sensors if they were put in front of the seeder. Results of the experiment are relevant to spatial parameterisation of existing soil models.

Simulation of realistic soils for 3-D computational models

This paper investigates the problem of simulation of realistic soils for electromagnetic 3-D computational models. The major difficulty is to take into account the heterogeneous nature of real-life soils, which is an aggregate of random and regular structures, due to environmental (climatic conditions, etc.) or human (soil tillage) processes. The developed methodology uses 3-D measurements of pertinent soil parameters, able to describe the heterogeneity of real-life soils. It can be broken down into four main tasks: (a) 3-D measurement of soil parameter(s); (b) characterization of the 3-D spatial distribution of soil parameter(s); (c) simulation of 3-D volumes with the same spatial distribution; and (d) simulation of 3-D soil permittivity maps using electromagnetic mixing model. This methodology is illustrated with the example of soil density measurement, which is evaluated with the use of a motor-driven penetrometer.

Design of lightweight airborne MMW radar for DEM generation. Simulation results

Abstract There is a growing need for lightweight airborne platforms that could provide precise information about the environment (topography, presence of obstacles, etc.) filling the data gap between aerial/satellite remote sensing and terrestrial systems. A major limitation of classical sensors such as vision or laser is that they are ineffective in degraded visual conditions. Millimeter-wave radar provides an alternative solution to overcome the shortcomings of optical solutions, because in the microwave range, data can be acquired independently of atmospheric conditions and time of the day. The intended application of a new radar sensor is the construction of digital elevation models of the overflown environments. As the design of new radar sensors for light airborne platforms is subject to specific technological constraints, a simulator of airborne radar surveys is developed. The objective of the simulator is to help the designer in defining the main parameters of the future airborne radar, and in developing radar signal processing algorithms.