6.5.1 Background and objectives
A theoretical assessment of the radar system performance was carried out before installation;
however the actual performance in a particular site depends heavily on the specific environment at that particular location. The specific radar location within the SWPP represents some extraordinary challenges for the radar. In addition to ground clutter, the echo from the large wind turbine struc-tures causes heavy interference which will mask the detection of smaller targets like birds if they happen to be in the same radar resolution cell. We have also experienced significant ground clut-ter behind the turbines, caused by energy being reflected off the turbine blades and the nacelle down to the ground behind the wind turbine and taking the same way back to the radar, creating stripes of ground clutter behind each turbine (see also paragraph 6.8). To investigate MERLIN per-formance at its current location within the SWPP, field trials with dedicated controlled targets have been performed. This effort was meant to serve several purposes:
Optimization of radar settings. The MERLIN processing functions have a set of parameters which can be adjusted to each operational task and environment. The flight tests provide data which helps in optimizing these processing parameters.
Provide the research team with detailed information on actual radar performance both to en-sure proper set-up of the various experiments and field surveys, and as an important prerequi-site to take into consideration when the bird flight data collected by the radar is analyzed later.
Provide a radar performance baseline for future quality control, e.g. before particular important recording periods, to ensure that the original performance is maintained.
The most important performance system capabilities to verify are:
Detection in the clear. I.e. the maximum detection range for a given size target only limited by system noise. This is the most basic and important performance capability of any radar sys-tem.
Target accuracy. The accuracy of the reported target position when it is recorded depend on two components: one random error that is due to statistical variation in receiver noise and in-fluenced by radar parameters like beam widths and the receiver noise factor, and one system-atic error due to misalignment of the radar to the surrounding terrain, usually both in bearing and range. The random component can only be measured and used as an important prerequi-site when data is analyzed. The systematic error can be measured and adjusted for so that it is removed in subsequent data recordings.
Target resolution. Quantification of targets requires knowledge of the resolution capability of the radar, i.e. the minimum distance between two targets with which the radar will still report two separate targets instead of one larger merged target.
Detection over ground clutter areas. A percentage of the surveillance (horizontal) radar cover-age on Smøla is influenced by unwanted echoes (clutter) from the wind turbines and the ground (see also paragraph 6.8). This clutter will reduce the detection capability of birds in the affected areas; it is however important to find out to which extent.
6.5.2 Test method
The main approach taken to radar-performance testing has been to use a controlled test target in live flight tests in the actual operational environment inside the SWPP area. To provide a realistic view on the actual performance with real targets, the test targets should correspond to the actual targets to be tracked as closely as possible in terms of radar cross section and flight behaviour.
The first trials were made using a small conducting sphere as the test target. To move the test
tar-(RCS), is accurately known for any given radar wavelength, and related to its radius with a simple formula. This would make it possible to test the radar with different size-test targets simply by us-ing different size spheres. Unfortunately the actual radar resolution, given by the extraction algo-rithms in the radar processor, was not narrow enough to allow for proper resolution with the towing aircraft at practical line lengths. In addition, towing a sphere behind a model aircraft poses a real challenge to the remote-controlling pilot on the ground, and places severe restrictions on the free-dom to manoeuvre and thus limiting the flight patterns possible to perform. Therefore this method had to be abandoned. Instead the model aircraft itself has been used as the test target.
A model aircraft has a relatively short visual control range and usually has to be kept within 500 m from the controlling pilot on the ground. To be able to conduct long-range radar tests, NINA has rigged a model aircraft with video camera and video transmitter (Figure 52). This enables flying beyond visual sight range. In august 2009 ranges in excess of 2 km from the pilot position where obtained. The aircraft is controlled on the 35 mHz band, and the onboard video transmitter is transmitting on the 2,4GHz band. The aircraft is controlled using video goggles, also known as First Person View (FPV) flying.
Figure 52. Model aircraft with video camera and transmitter used for radar-performance testing.
Photo: Pål Kvaløy.
This technique provided the freedom to design and perform virtually any test-flight pattern within the SWPP area. In addition, an on-board GPS logger accurately recorded the aircraft position dur-ing the flight. The recorded GPS data was later compared to the target position reported by the radar for the same flight, and served as an aid to do both accuracy and detection analysis.
To be able to find the detection performance for a given bird size, the model aircraft RCS had to be compared to the RCS data of the species in question, and the detection range found for the aircraft was therefore used to calculate the corresponding theoretical detection range for the given bird RCS. Simple models for the RCS of different bird species can be found in the literature, and the necessary extrapolation of detection range is a trivial task using the radar equation, but it requires that the size of the test target is known, and preferably that it is in the same order of magnitude as the RCS of the birds the radar is set to detect and record. Even thought the model aircraft equipped with a GPS receiver and video link provided the necessary freedom to move the test tar-get around producing good GPS reference data for analysis, the drawback of the method was that the aircraft is a relatively complicated structure with a complex and unknown RCS. As opposed to
the RCS of a conducting sphere, the aircraft RCS will vary substantially as a function of the radar wavelength and the aspect angle. This is due to the irregular shape and positioning of the different scatterers inside and outside the balsa tree fuselage. An important prerequisite when using the model aircraft as a test target was therefore that its RCS was measured and verified for all the relevant aspect angles and radar wavelengths. This was performed using a special RCS meas-urement set-up in the anechoic chamber in the NTNU/SINTEF laboratory for antenna measure-ments. Figure 53 below shows the model aircraft mounted in the lab, and has an example of a 360° S-band RCS measurement.
Figure 53. Model aircraft used as test target mounted on the swivelling table on the measurement tower in the anechoic chamber. Measured S-band RCS on the right. Photo: Yngve Steinheim.
6.5.3 Performance test results
One of the important tasks to perform initially was to align the horizontal radar with the environment so that the digital target data was reported with its correct geographical position. To do this the target data recorded in the radar was compared to GPS data, and the offset was estimated and compensated for. Figure 54 illustrates an example of recorded radar tracks together with the GPS aircraft position data. In addition to low visibility in parts of the route, this example clearly indicates that there is a position offset between the radar reports and the GPS data from the test aircraft. This information is used to perform proper alignment of the radar.
Figure 54. Radar tracks (red dots) together with the corresponding GPS position of a model air-craft (black solid line) used for radar-performance testing.
Because of a highly cluttered environment, the probability of detection (Pd) is generally lower than in the clear in the whole coverage area. The maximum detection range has been estimated com-bining 5 different test-flights (tracks) of the model aircraft in Figure 55.
Figur 55. Probability of detection of the test aircraft as a function of range. The grey bars indicate the actual binned data and visually assessed detection range (2350 m).The su-perimposed smoothed lines indicate the mod-elled effect and the detection range at Pd=0.5 (2050 m, range: 1650 2550 m).
Figure 56. Estimated detection range (Pd=0.5) for different bird species based on the modelled detection range of 2050 m. The striped lines indicate the uncertainty in the estimated detection range (S.E.).
The clutter reduces the probability of detection inside the clutter patches in the coverage area, and the result is that the probability of detection is not a smooth function of range, but Figure 55 clearly indicates that it is decreasing with range. And the point where we have Pd=0.5 for the test aircraft lies between 2050-2350 m. With this information, and since we know the aircraft RCS and the theoretical RCS of different bird species, we can use the radar equation and extrapolate some estimated detection ranges with the horizontal S-band radar for different sized birds. From Figure 56 we see that we should expect to be able to follow the WTE with a Pd of 0.5 out to about 1500-1700 m. That will give a coverage area about 3000-3400 m in diameter for this particular species.