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The collected stellar radiation is transferred by the telescope optics to the polarimetric modulator As a result, the initial polarization may be altered before it is measured by the instrument attached at the telescope s focus The most common spurious effect is that any collected unpolarized light becomes weakly polarized The amount of polarization introduced is referred to as the instrumental polarization There may be additional sources contributing to the instrumental polarization other than the telescope mirrors It is usual practice in any observing programme to investigate the instrumental polarization by making measurements of unpolarized standard stars The mean values of the NSPs for these measurements may be represented by q I and u I , and the position of the instrumental polarization can be plotted in a normalized Stokes vector diagram For measurement of other stars, the reduction procedure involves shifting the origin, O, of the measurements to that of the instrumental polarization position, O0 (see igure 55) This is best done by subtracting the offset, q I , u I , from the q, u values of the program stars The process corresponds to a vector subtraction of the instrumental offset by the inversion of the principle of the Additivity Theorem for Small Polarizations (see Section 45) If the source of instrumental polarization is identi able as occurring in the telescope fore-optics, and can be expressed as a Mueller matrix, a more accurate reduction would involve an inversion procedure to obtain revised values according to the elements of this matrix In the simplest case, the matrix would be that of a weak polarizer; in some cases, there may also be a small phase change introduced by the optics and this would need to be incorporated into the matrix (see further discussion in 7) It is also possible that the telescope optics effect a depolarization to any collected polarized light (see Section 74), this being a true reduction of a degree of polarization and not simply a linear-to-circular conversion Depolarization is a dif cult parameter to investigate, the best that can be done is to inter-compare results taken by different instrumental setups If its effects on all the Stokes parameters are known, and are expressible in the form of a Mueller matrix, in principle, any.

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Also, cryptography techniques can be used to provide a layer of security for all three localization system components (Distance/Angle Estimation, Position Computation, and ocalization Algorithm), explained in Section 183, by providing authentication Using Barcode generator for Visual Studio NET ontrol to generate, create bar code image in VS NET applications In these cases, the next layer of defense would be to make the nodes hemselves detect and block the compromised factors One way to make this happen and to defend against a possible attack is to observe the behavior of the nodes over time and decide whether to trust them These techniques can be used mainly to protect the Position Computation component, since information gathered from untrusted nodes can simply be ignored when computing the position of the nodes For instance, in Liu et al [28] it is proposed a set of techniques for detecting malicious beacon nodes.

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One technique detects malicious beacon nodes by comparing the distance estimated by using the location information provided by these beacon nodes and the distance estimated by means of the signal (eg, RSSI, TDoA, AoA) Another technique evaluates the round-trip time (RTT) between two neighbors, based on the observation that the replay of a (malicious) beacon signal introduces extra delay Then, the base station (or sink node) uses such information about malicious beacons to reason about the suspiciousness of each beacon node, and then it lters out malicious beacon nodes accordingly Srinivasan et al [29] extends the techniques proposed by Liu et al [28] by using a continuous scale and a reputation- and trust-based mechanism The result is the Distributed Reputation-based Beacon Trust System (DRBTS), which is a distributed security protocol for excluding malicious beacon nodes.

In DRBTS, each beacon node monitors its neighborhood for suspicious beacon nodes and provides information by maintaining and exchanging a Neighbor-Reputation Table, in such a way that other sensor nodes can choose trustworthy beacons based on a voting approach 1843 Robust Position Computation Robust position computation can be used in order to increase the security of a localization system This technique can be used when both cryptography and misbehavior detection is compromised In this case, a way to deal with malicious nodes is to accept that they will be present in the network and propose robust position computations that can still work in the presence of bogus information This is done mostly by using statistical and outlier ltering techniques In these cases, it is assumed that the benign nodes outnumber the malicious ones.

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