This thesis presents a study into nonlinearities in the radar receiver and investigates
advanced digital signal processing (DSP) techniques capable of mitigating the resultant
deleterious effects. The need for these mitigation techniques has become more prevalent
as the use of commercial radar sensors has increased rapidly over the last decade. While
advancements in low-cost radio frequency (RF) technologies have made mass-produced
radar systems more feasible, they also pose a significant risk to the functionality of the
sensor. One of the major compromises when employing low-cost commercial off-theshelf
(COTS) components in the radar receiver is system linearity. This linearity trade-off
leaves the radar susceptible to interfering signals as the RF receiver can now be driven
into the weakly nonlinear regime. Radars are not designed to operate in the nonlinear
regime as distortion is observed in the radar output if they do. If radars are to maintain
operational performance in an RF environment that is becoming increasingly crowded,
novel techniques that allow the sensor to operate in the nonlinear regime must be developed.
Advanced DSP techniques offer a low-cost low-impact solution to the nonlinear
receiver problem in modern radar. While there is very little work published on this topic
in the radar literature, inspiration can be taken from the related field of communications
where techniques have been successfully employed.
It is clear from the communications literature that for any mitigation algorithm to be
successful, the mechanisms driving the nonlinear distortion in the receiver must be understood
in great detail. Therefore, a behavioural modelling technique capable of capturing
both the nonlinear amplitude and phase effects in the radar receiver is presented before
any mitigation techniques are studied. Two distinct groups of mitigation algorithms
are then developed specifically for radar systems with their performance tested in the
medium pulse repetition frequency (MPRF) mode of operation. The first of these is the
look-up table (LUT) approach which has the benefit of being mode independent and computationally
inexpensive to implement. The limitations of this communications-based
technique are discussed with particular emphasis placed on its performance against receiver
nonlinearities that exhibit complex nonlinear memory effects. The second group
of mitigation algorithms to be developed is the forward modelling technique. While this
novel technique is both mode dependent and computationally intensive to implement,
it has a unique formalisation that allows it to be extended to include nonlinear memory
effects in a well-defined manner. The performance of this forward modelling technique
is analysed and discussed in detail.
It was shown in this study that nonlinearities generated in the radar receiver can be
successfully mitigated using advanced DSP techniques. For this to be the case however,
the behaviour of the RF receiver must be characterised to a high degree of accuracy both
in the linear and weakly nonlinear regimes. In the case where nonlinear memory effects
are significant in the radar receiver, it was shown that memoryless mitigation techniques
can become decorrelated drastically reducing their effectiveness. Importantly however, it
was demonstrated that the LUT and forward modelling techniques can both be extended
to compensate for complex nonlinear memory effects generated in the RF receiver. It was
also found that the forward modelling technique dealt with the nonlinear memory effects
in a far more robust manner than the LUT approach leading to a superior mitigation
performance in the memory rich case
