What is the difference between tracking and homing

Viewing 4 posts - 1 through 4 of 4 total. August 8, at pm Make it make sense, please. There is only one answer. Your problem is solved. August 13, at pm The tracker put on the Falcon was a basic transmitter.

Image Source: www. A hold or hold pattern is a racetrack defined by inbound course to a fix, a turn direction and turn time, usually given in minutes. Depending on from where you are trying to enter a hold, there will be different hold entry techniques.

Sign up to join this community. The best answers are voted up and rise to the top. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Learn more. What are the meanings of these terms related to instrument flight? Ask Question. Asked 6 years, 7 months ago. Active 6 years, 7 months ago. Viewed 4k times. Any one to suggest a thorough instrument book as well.

A previous study estimated m as pigeons' perceptual range for flocking [ 17 ], so these five pairs that split would have been out of range for a large proportion of the homeward track.

Tracks of pairs of homing pigeons and their previous solo routes. In each panel, black lines show a pair's GPS tracks and shaded lines show the two birds' previous solo tracks, illustrating the conflicts that arise due to differing route preferences.

Ground speed is plotted along the solo tracks, smoothed using a 4 s moving average. Online version in colour. We tested the error in GPS measurements of relative position and direction by fixing two trackers to a pole, 1 m apart, and carrying the pole on a bicycle back and forth along a straight track approx. We repeated the procedure with the pole either perpendicular or parallel to the direction of travel. The total error in measuring relative position was somewhat larger median 1.

The total error is consistent over a timescale of minutes and therefore has little effect on direction measurements. This validates the claim in previous studies that velocities measured from GPS have less error than positions [ 16 ]. We converted latitude and longitude to metres using a Universal Transverse Mercator projection and excluded points before takeoff or after landing.

We analysed flocking responses in the combined data from all paired flights. Interaction variables calculated from the pigeon tracks and from the simulation. We calculated all variables in the horizontal plane, because the horizontal dimension contains most of the variation between homing routes and is therefore more relevant to route choice.

As a second method of analysing leadership, we analysed the position of the paired routes relative to the preferred solo routes of the two birds. We calculated the distance, d i from a bird's position during a paired flight to the nearest point on its previous solo route. We excluded portions of track where the solo routes were converging, for example, when nearing home, which might cause a pair to move towards j 's route even when following i 's route and regardless of j 's influence.

If the pair split it is meaningless to classify either as a leader or follower, so we restricted the analysis to times when the pigeons remained within m of each other perceptual range of flocking estimated by Biro et al.

To investigate individual differences that might predict a bird's position and influence in a pair, we analysed speed and route fidelity in the five solo tracks preceding each paired flight. First, we discarded portions of the solo tracks within m of the release point or the home loft. We calculated instantaneous ground speed along the remaining portion of the track.

We quantified route fidelity using the method of Freeman et al. At each point on the mean path, the spatial variance is.

Having calculated speed and variance, we compared these solo-flight variables to behaviour in a pair front—back positioning, influence over route choice. To make the comparison using solo-flight variables from a nearby part of the landscape, we started with a point on the paired track, found the nearest point on each of the pigeon's five preceding solo tracks, and used the mean speed from those five points.

Similarly, we used the variance from the nearest point on the mean path. We tested the significance of relationships between solo and pair flight variables using a randomization test, in which we randomly assigned a set of solo tracks to each pair track and then repeated the analysis.

The sets of solo tracks each consisted of five consecutive tracks from the same bird, randomly chosen without replacement from the sets preceding paired flights.

Turning was strongest when the neighbour was directly left or right of the focal bird figure 3 c. Rather than being mediated by attraction, this alignment response is in addition to the effect of the neighbour's position figure 3 e. In these plots, the focal bird is at the origin, facing up.

As shown in i , some bins contain very few occurrences of the neighbour and are therefore more likely to assume extreme values. Positive or negative x -axis values indicate that the neighbour was, respectively, in front or behind the focal bird.

Note that the bins are not of equal area. Error bars in b, c, d, g and h show the standard deviations of bin-means from bootstrap replicates, created by randomly sampling the 23 birds, with replacement. Changes in speed also mediate flocking. When the neighbour was more than 2 m in front in the direction of travel, a pigeon tended to speed up, but otherwise tended to slow down figure 3 f , g.

This forward bias is also prevalent in the fact that the rate of acceleration towards a neighbour in front is higher than the rate of deceleration towards a neighbour behind figure 3 g. An immediate result of these various flocking responses was that pairs most frequently flew side by side i. Bootstrap standard errors figure 3 b , c , d , g , h indicate that these responses are observed robustly across subjects.

In addition to the flocking interaction, we found that each bird was also attracted towards its preferred route. In some cases, the pigeons flew down the established route of one of the birds, and in other cases they took compromise routes figure 1. We calculated the percentage of time that the partner and the nearest point on the previous route were on opposite sides of the focal bird, combining data from both birds to give one data point per paired flight.

It is further evidence that the birds flying in pairs continued to respond to landmarks along their previous solo routes.

The partner and the preferred route are still on the same side a large portion of the time, which is expected given that the pairs did not always fly in between the two preferred routes, and portions of the paired flights have very little conflict of information figure 1.

We quantified route attraction during solo flights, when there was no confounding influence of conspecifics. The intensity of turning in the direction of the previous solo route was maximized when the bird was approximately m from the nearest point on its previous route see electronic supplementary material, figure S1. This shape of route response is probably because pigeons tolerate small perturbations within a route corridor but are increasingly motivated to return to the route after larger perturbations [ 25 ], counteracted by reduced visibility of landmarks over hundreds of metres.

To avoid introducing extra parameters, we made the simplifying assumption that a pigeon is attracted to the nearest point on its preferred route, when in fact a pigeon displaced from its preferred route is more likely attracted to a point downstream, i. Our approximation realistically captures the behaviour of a pigeon flying roughly parallel to its preferred route, first because attraction either to the nearest point or to a downstream point will generally require turning in the same direction, and second because repeatedly making small turns towards the nearest point will result in the bird re-joining downstream.

To test our understanding of how the birds interact with each other and their environment, we developed an SPP model based on the interaction rules inferred from figure 3. Our model builds on those by, for example, Vicsek et al. In the model we now propose, we also incorporate the speed changes observed in the pigeons, rather than assuming constant speed.

The model allowed us to test the sufficiency of the inferred rules for reproducing patterns of paired movement—both local flocking geometry as well as the decision-making properties of the pair when they had conflicting route information. Furthermore, we could use the model to test the effects of individual differences on the decision outcome, even if these individual characteristics were not directly manipulated in the experiment.

In the model, each bird turns in response to the neighbour's orientation and position and alters its speed to draw level with a neighbour in front or behind. Each bird has its own preferred route, which it will fly towards in the absence of a partner. To simulate a conflict of information, the two preferred routes are assumed to be straight lines that originate at the release point and continually diverge with an angle of 0.

Typical trajectories in separate runs of the simulation of two birds with different preferred speed. Diverging straight lines: preferred routes; curved lines: paired flights.

The preferred speed of bird 1 is , which is equivalent to the average speed in the experiments. The preferred speed of bird 2 is The faster bird can effectively lead the pair towards its preferred route.

Each of these angles are small and represent the various forces acting on the bird. Below we provide details about the form of each of these components. The attraction response function in equation 3. Both the value of a sl and a are obtained by fitting equation 3. Since the focal individual turns away from very close neighbours and towards more distant neighbours figure 3 b , we use a sigmoidal function of distance to modulate the transition between repulsion and attraction.

Bird 1's preferred speed was set to the mean experimental value of The forms of equations 3. These differences are justified by the observation that a fraction of the measured variability was due to GPS noise and did not reflect real variability in the position and movement of the pigeons. These simple rules reproduce qualitatively many of the observed features of interactions between real birds.

In the simulations, as in the data, birds typically flew side by side figure 5 i. Some less intuitive aspects of the empirically observed interactions also appeared in the simulation output. The simulation demonstrates that this behaviour can arise without any explicit avoidance response to a neighbour behind, and instead it is due to the higher relative influence of the preferred route once the neighbour enters the blind angle.

In the empirical data, the focal bird also presented an acceleration response when the neighbour was directly behind figure 3 f,h , whereas there was no such acceleration in the simulation figure 5 f,h.

This acceleration response might arise if real birds accelerate in response to the preferred route, something we did not implement in the simulation. Error bars in b, c, d, g and h often smaller than symbol size show standard errors based on the number of points in each bin.

The other plots in figure 5 are qualitatively similar to the corresponding plots in figure 3. Most differences between the two figures stem from the fact that in the simulation the birds are always in a conflicting situation. For this reason, simulated birds are observed to turn away from neighbours positioned behind them with greater intensity than real birds. This higher level of conflict in the previous routes also decreases the total signal in figure 5 b. Furthermore, the intensity of the responses observed from the simulation did not match the data exactly e.

Response intensity in the simulations could be manipulated by increasing or decreasing the noise parameter, but the sign of the response typically remained stable. For readers interested in testing combinations of parameters different from those reported in the figures, we make available a commented version of the Matlab simulation code as electronic supplementary material. In the model, we assume that each bird has its own preferred speed of flight, with one bird slightly faster than the other.

The two simulated birds converged on a common speed, but the bird with faster preferred speed was more frequently positioned in front figure 6 a. The model further predicts that, because alignment and attraction are forward biased i. We quantified leader-follower asymmetry using two metrics that reflect different scales of decision-making. On a small spatial and temporal scale, we quantified influence over momentary changes of direction using directional correlation delay [ 16 ].

In the simulations, the bird in front tended to initiate turns and was followed by its neighbour behind figure 6 b. On a more global scale, we tested which bird dominated the pair's choice of route. In simulations without a blind angle, getting in front did not give a bird more influence, either measured using directional correlation delay figure 6 d or from the global route decision figure 6 c.

Properties of pigeon movement visualized from the simulation a—d and the data e—f. Birds with faster preferred speed tend to position in front during the simulated paired flights. The bird in front usually changes direction first and the bird behind follows. Symbols show proportion of simulations that bird 2 dominated, for each of 20 equally spaced bins. The faster bird is significantly more likely to dominate the decision, but only if there is a blind angle. Leadership does not depend on position.

In b , d and f , negative delay indicates that the focal bird adopts a particular direction after its partner, whereas positive delay indicates that the focal bird adopts a direction before its partner. These predictions are confirmed in the data.

Because solo speed varies along the route figure 1 , we compared pair behaviour to nearby portions of solo track see Material and methods. The bird in front also had a positive directional correlation delay time, indicating that it tended to lead momentary changes in direction figure 6 f.