The algorithm of lengthened objects detection is based on statistical processing of reflected pulse altimeter signal. The method of maximum posteriori probability is applied to make a decision. Minimum of maximum posteriori probability is accorded with lengthened objects position. This fact is taken into account to detect the objects' position. This algorithm allows autonomic navigation to be implemented. Two cases of the algorithm implementation are shown in this article. The first method is based on the unsharpened beam regime of radar altimeter and the second is based on the application of the Doppler's filtration. The results of flight experiments proving the correctness of the created algorithm are introduced in this article.
The model experiment is organized according to the Fig. 2. as follows: UVA is moving from the “terrain I” across the
“terrain II” to the “terrain I”, here the “terrain II” is LO. In Fig. 2 it is marked the next: D – the LO width, L – the
exposure spot width, Θ – the LO’s orientation angle. As the result of signal accumulation for each, the UVA’s position is
identified (there were more than 10 000 envelope counts per the UVA’s position), used for the probability estimation
evaluation.
The combinations of typical terrains, which are applicable for LO detection are described in [
The results of the model experiment in the case of “forest/asphalt” are shown in Fig. 3.
According to the Fig. 3, the real borders are shifted symmetrically to the borders detected by the algorithm. It is explained by the minimum shift of posteriori probability function to the side of the less reflective terrain. The minima of the posterior probability detect the border between typical terrains which can be evaluated by the shift error (in Fig. 3 the shift error is about 15% of the exposure spot width), and the minimum probability of the correct detection is 0,8. The results of the model experiments for LO detection are introduced in the Table 1 for the case with Θ=[30˚;90˚] and different signal/noise ratio.
The Table 1 makes it possible to choose the terrain’s combinations which could be distinguished during the flight by
the pulse altimeter. As the result, the best LO for the algorithm is the “water” surface with the background of the
scattering terrains such as “meadow” or “forest”. This result is similar to the point in [
SN=20dB SN=30dB D=0,1L D=0,8L D=0,1L FAF FAF FAF FWF FWF FWF
GWG
D=0,8L FAF FWF
GWG BWB MWM
BWB
MWM BWB MAM MWM SWS WGW WMW WSW AFA WFW AGA AMA GAG
BWB MAM MWM SWS WGW WMW WSW AFA WFW AMA GAG
In the Table 1 following abbreviations are used: SN – signal/noise ratio, А – asphalt, B – bushes, C – concrete, F – forest, G – grass, M – meadow, N – ground, S – snow, W – water. For example, the abbreviation FAF is equivalent to the combination “Forest-Asphalt-Forest”. Shadowed combinations with high false detection probability of the LO are also presented in the table. It can happen because of signal and noise nature, being not the matter of importance for the algorithm it does not matter. These cases have to be excluded from the study.
Table 1 can be used to choose the LO, for designing recommendations and while choosing the UVA route. 3
The application of the Doppler filtration (DF) as the method of increasing the algorithm’s spatial resolution for solving the problem of LO detection is shown in this part of the reserch.
According to [
Three series of experiments were conducted for the test. In the first range of the experiments, the orientation of the
Doppler filter (see fig. 4) was changed and the probability of the correct discrimination of the terrain was estimated [
In Fig. 5 the results of the model experiments are shown. It was obtained that the maximum posteriori probability could be gained according to the position in Fig. 4, which is marked with Δ1.
Similarly, the other experiment was conducted. The width of the Doppler’s filter’s stripe was changed to the optimal angle, which was obtained in the previous experiment. As the result, it was achieved that the minimal d (0,2L) provides the maximum posteriori probability. Here is d – the Doppler stripe width; L – the exposure spot width.
So, during the test it was obtained that the DF provides better discrimination for terrains if the width of the Doppler stripe is small (d≤0,2L) and the direction of the exposure is corresponded to nadir direction.
The application of the Doppler filtration provides the increasing of the spatial resolution for the radar altimeter. It allows us to detect narrow LO, but simultaneously it can prevent us from the detection if the angle φ in Fig. 6 is small.
The third experiment was about LO’s orientation. Fig. 6 shows the relative part of the LO in the Doppler’s filter’s stripe (m) from the angle of the LO (φ)orientation . The model experiment showed that the maximum influence in the reflected signal delivered by the LO is oriented co directional to the Doppler stripe. If the angle is φ=30˚, the part of the LO decreases by half. As the result we suggested that the advantages of the DF are applicable only if φ≥30˚. In this case maximum posteriori probability gained if φ=90˚.
The similar to [
The information in the Table 2 provides the detection of LO with the probability of correct discrimination higher than 0,6 if φ is changed from 30˚ up to 90˚. As the result, it is shown that the change of the signal/noise ratio leads to the change of typical LO number which can be detected by the algorithm (decreasing leads to the increasing of the LOs), also the increasing of the LO width leads to the LOs number increasing. 4
The information from the experiments [
To conduct the flight experiment, the information was obtained from pulse radar altimeter [
The comparison of the current model experiments’ results with the typical regime for pulse radar altimeter shows that DF allows us to distinguish approximately twice typical LOs than typical regime.
In this article the significant results were obtained: 1. Two cases of the created algorithm application were examined: the pulse radar altimeter with unsharpened beam and the narrowed beam by the DF. It was shown that the regime of Doppler filtration allows us to increase the number of detected terrain’s combinations at least twice. For example, if DF is used, the algorithm can detect next terrain combinations (with narrow “water”) “Bushes/water/bushes”, “Grass/water/grass” and so on. 2. The flight experiments validated the correctness of the created algorithm. It is obtained, that the combination of unsharpened beam and DF algorithms allow us to detect more than 60% of the narrow “water” objects, “meadow”, “ground” and “forest” objects can also be found 3. The results of the current investigation allow us to choose the lengthened objects which are suitable for the UVA navigation. It is shown that the terrain combinations “water/forest” and “asphalt/forest” provide the maximum of the correct discrimination probability if LO is oriented to the flight direction with the angle from 30 up to 90 degrees and the signal/noise ratio is not less than 0dB.