Simulating Coherent Radar Returns

The above steps are necessary to obtain a clutter scene relative to the position of a radar system. The data is thus representative of the radar observed environment information (environment model) which includes the clutter patches, each with an associated LOS visibility from the radar, height, area, distance from the radar, grazing angle (including incidence and depression angles), and the terrain class that the patch matches to the closest (based on the Land Cover data chosen). Using environment model information, land clutter models can be used to provide a backscatter coefficient value for each visible clutter patch. The reflectivity (including the inherent pattern propagation factor F4) for each clutter patch can be determined to create the land clutter model characteristics of the scene.

This only represents the radar observed environment, LOS coverage, and the reflectivity. The objective of simulating site specific radar land clutter returns can not be achieved

without the application of a radar sensor model, including the antenna beam pattern. The radar sensor contains information about the radar characteristics including but not lim- ited to, radar operating frequency, waveform, radar resolution and range limits, antenna pattern, transmit and receive gains, radar position, height, and orientation, radar system losses etc. The mapping of the radar antenna beam pattern onto the scene and coherent addition of returns from the clutter patches would be the next step.

The modelling of coherent radar returns would firstly require the radar observed envir- onment and land clutter model that was developed. The radar antenna beam pattern is modelled in both azimuth and elevation. The visible terrain data that is within the radar antenna beamwidth would be computed. Range traces are then formed at closely spaced azimuth angles which is based on the radar antenna beamwidth, scan rate, and pulse re- petition frequency (PRF). The azimuth spacing needs to be chosen such that it provides adequate fidelity. The range samples are then calculated and spaced according the radar range resolution. Area sampling is performed for each range trace. For each range trace, all samples within the radar range bin is summed to simulate coherent radar return. The returns are modified by the attenuation relative to the antenna peak gain at boresight as a function of the off boresight sample angle. The land clutter power at the receiver for each range bin is then calculated using the radar equation.

3.4

Chapter Summary

In this chapter, several existing land clutter models, DEM and LC data sources were investigated.

A description and analysis of several existing land clutter models are presented in section 3.1. A summary of these land clutter models are presented in Table 3.9 above. Further analysis and comparisons of these land clutter models are investigated in section 4.1. A description and analysis of several DEM and LC data sources are presented in section 3.2. It is recommended that the SRTM 30 m DEM dataset and the GlobeLand30 LC dataset should be used in a site specific radar coverage and land clutter modelling tool as they are currently the highest quality DEM and LC datasets that are freely available that covers all intended areas of interest. A summary of these DEM and LC data sources are

presented in Table 3.14 and Table 3.15 respectively.

Section 3.3 presents a meshing technique that can be used to simulate clutter patches in a site specific radar coverage and land clutter modelling tool. The process involves breaking up the DEM height points into triangular surface areas, each representing a clutter patch from which various calculations can be performed. Earth curvature and atmospheric refraction effects can be reduced by using the 4₃ Earth Model. Section 3.3.2 presents a terrain LOS visualisation technique known as ray tracing that can be used in a site specific radar coverage and land clutter modelling tool to determine masked areas. A discussion and brief analysis on the required simulated clutter cell size, DEM resolu- tion, and DEM height accuracy. is given in section 3.3.3. This analysis further justified the recommendation to use the SRTM 30 m DEM dataset in a site specific radar coverage and land clutter modelling tool.

Furthermore, a process for simulating coherent radar clutter returns is given in section 3.3.4.

Chapter 4

Analysis and Results

This chapter provides a discussion of the land clutter / backscatter coefficient models in the context for use in a site specific radar coverage and land clutter modelling tool. It aims to determine which of the existing models are the most appropriate to use for the varying simulation cases, as well as to identify categories of land clutter models where little or insufficient models are available. It also aims to provide the link between the different terrain classes described in land cover data compared to those in land clutter / backscatter coefficient models. Land clutter and land cover link results will be illustrated and tabulated in aid of developing algorithms for use in a site specific radar coverage and land clutter modelling tool. It ends by proposing a guide on the process to follow for the development of a site specific radar coverage and land clutter modelling tool.

4.1

Analysis of Land Clutter Models

This section provides an analysis of the various land clutter models discussed in this dissertation. The aim is to determine how well site specific simulated clutter using the land clutter models agree with measured data, and which models are best suited to use for the various grazing angle regions. The process will be based on information gathered from literature for low grazing angles, and from comparing simulated clutter using the land clutter models with measured data for angles in the plateau and high grazing angle region. This information does not aim to fully validate the various land clutter models considered in this dissertation for all cases, but rather aims to determine whether the

assumptions made in section 3.1 about the compatibility (strength) and validity of these models are valid for a few cases.