Position, Navigation, and Timing Technologies in the 21st Century. Группа авторов. Читать онлайн. Newlib. NEWLIB.NET

Автор: Группа авторов
Издательство: John Wiley & Sons Limited
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Жанр произведения: Физика
Год издания: 0
isbn: 9781119458517
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alt="images"/>, the receiver refines and maintains these estimates via tracking loops. A phase‐locked loop (PLL) or a frequency‐locked loop (FLL) can be employed to track the carrier phase, and a carrier‐aided delay‐locked loop (DLL) can be used to track the code phase. FLLs are generally more robust than PLLs, are useful when transitioning from acquisition to tracking, and can track in more challenging environments [54, 55]. Figure 38.12 depicts a block diagram of a PLL‐aided DLL tracking loop [12, 18]. The PLL and DLL are discussed in detail next.

Schematic illustration of cellular CDMA signal acquisition front panel showing Zk2.

      Source: Reproduced with permission of IEEE.

Schematic illustration of the tracking loops in a navigation cellular CDMA receiver.

      Source: Reproduced with permission of IEEE.

      PLL: The PLL consists of a phase discriminator, a loop filter, and a numerically controlled oscillator (NCO). Since the receiver is tracking the data‐less pilot channel, an atan2 discriminator can be used, given by

equation

      where images is the prompt correlation. The atan2 discriminator remains linear over the full input error range of ±π and could be used without the risk of introducing phase ambiguities. In contrast, a GPS receiver cannot use this discriminator unless the transmitted data bit values of the navigation message are known [54]. Furthermore, while GPS receivers require second‐ or higher‐order PLLs due to the high dynamics of GPS SVs, lower‐order PLLs could be used in cellular CDMA navigation receivers. It was found that the receiver could easily track the carrier phase with a second‐order PLL with a loop filter transfer function given by

      DLL: The carrier‐aided DLL employs a non‐coherent dot‐product discriminator given by

equation

      where Λ is a normalization constant given by Λ = Tc/2C; C is the carrier power, which can be estimated from the prompt correlation; and images, and images are the prompt, early, and late correlations, respectively. The prompt correlation was described in Section 38.5.2.1. The early and late correlations are calculated by correlating the received signal with an early and a delayed version of the prompt PN sequence, respectively. The time shift between images and images is defined by an early‐minus‐late time teml, expressed in chips. Since the autocorrelation function of the transmitted cellular CDMA pulses is not triangular as in the case of GPS, a wider teml is preferable in order to have a significant difference between images, and images. Figure 38.13 shows the autocorrelation function of the cellular CDMA PN code as specified by the cdma2000 standard and that of the C/A code in GPS. It can be seen from Figure 38.13 that for teml ≤ 0.5 chips, Rc(τ) in the cdma2000 standard has an approximately constant value, which is not desirable for precise tracking. A good rule of thumb is to choose 1 ≤ teml ≤ 1.2 chips.

      The DLL loop filter is a simple gain K, with a noise‐equivalent bandwidth images Hz. The output of the DLL loop filter vDLL, k is the rate of change of the code phase, expressed in s/s. Assuming low‐side mixing, the code start time is updated according to

equation Graph depicts the autocorrelation function of GPS C/A code and cellular CDMA PN sequence according to the cdma2000 standard.

      Source: Reproduced with permission of IEEE.

      In a GPS receiver, the pseudorange is calculated based on the time a navigation message subframe begins, which eliminates ambiguities due to the relative distance between GPS SVs [55]. This necessitates decoding the navigation message in order to detect the start of a subframe. These ambiguities do not exist in a cellular CDMA system. This follows from the fact that a PN offset of one translates to a distance greater than 15 km between BTSs, which is beyond the size of a typical cell [56].

      Finally, the pseudorange estimate ρ can be deduced by multiplying the code start time by the speed of light c; that is,