Digital Signal Processing Reference
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correlation loops of the receiver, utilizing the signal, jamming, and noise relative power
underlying satellite geolocation application, and incorporating the navigation receiver
information on polarization and spatial signatures of the satellites. Although focused
on GPS, the approaches presented are applicable to Global Navigation Satellite Systems
(GNSS), including Galileo, GLONASS, and Beidou [6]. All GNSS share the same oper-
ating principle. The receiver position is computed based on the distances between the
receiving antenna and a set of satellites, and the receiver determines these distances by
measuring the propagation time of the signals transmitted by the satellites. This propa-
gation time can be obtained from the delay (referred to as pseudorange or code phase) of
the complex envelope and from the carrier phase.
Dual-polarized beam-steering antenna array receivers are considered. We discuss the
modeling and performance of optimum and adaptive antijam receivers implementing
constrained minimization techniques.
14.2
Background
The Global Positioning System (GPS) is a satellite-based system used in localization and
navigation for both military and civilian applications [7, 8]. It employs direct-sequence
spread spectrum (DSSS) on two carriers, L1 at 1575.42 MHz and L2 at 1227.6 MHz. Each
GPS satellite broadcasts a C/A code with chip rate at 1.023 Mchips/s or a precision (P)
code at 10.23 Mchips/s. New navigation signal and code structures are considered, aim-
ing at improving receiver positioning and combating multipath [6].
Depending on the operating environment, the signal-to-noise ratio (SNR) at the GPS
receivers can be as low as -30 dB. For a strong interference, the jammer-to-noise ratio
(JNR) may exceed 30 dB, which will severely degrade the GPS performance and the
code synchronization process. Although the spread spectrum modulation provides
some antijamming protection to weak signals, a high power interference (e.g., more than
5 dB above the noise) cannot be suppressed adequately by the spreading gain, causing
inaccurate tracking and positioning errors. Many antijam mitigation techniques have
been proposed, which are based on temporal processing [9-11], spectral-based process-
ing [12-14], subspace projection [15], and spatial signal processing [1, 16, 17]. Combina-
tions of the above techniques, such as time-frequency processing [18] and space-time
processing [19, 20], provide superior jammer suppression compared to single-antenna
or single-domain processing.
Adaptive techniques are commonly adopted for fast antijam implementations [21-30],
and shown to be effective in spatial discriminations and interference nulling. The array
response is continuously adjusted so that the interferers have low receiver gains. For
spatial-only processing, each antenna is allocated a complex weight, which is adaptively
chosen to minimize a desired cost function subject to satisfying a single or a set of desir-
able constraints. The two main types of adaptive antenna arrays are the nulling arrays
[1, 4] and the beam-steering arrays [2]. In both arrays, interference cancellation can
be achieved, irrespective of the signal temporal properties. It is noted that the MVDR
method incorporates knowledge of the directions of arrival (DOAs) of the GPS signals
to form beams toward the GPS satellites, while placing nulls toward the directions of
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