The need to see without being seen has been the cardinal principle of military commanders since the inception of warfare. Until the advent of World War II, the only means available to commanders from this point of view was espionage and intelligence gathering missions behind enemy lines. Just prior to World War II, the allies came up with a ground breaking invention, the pulsed radar. This invention radically altered the equation and for the first time in the true sense of the term one could see without being seen. The word RADAR is an acronym for Radio Detection And Ranging. As it was originally conceived, radio waves were used to detect the presence of a target and to determine its distance or range. The pulsed radar could sight the German lighter formations well before they reached the English coast and could, therefore, concentrate allied lighter groups where they were most needed. The German lighters were not even aware that they were detected. In effect, the pulsed radar acted as a force multiplier and helped the allies defeat the vastly superior Luftwaffe in the Battle of Britain. The allies pressed home their advantage of having the radar, by going on to win the Battle of the Atlantic against the German U-Boats by catching them unawares on the surface at nighttime when they were charging their batteries. This was truly stealth warfare in the purest sense of the term. The German reaction to these events was slow and by the time they came up with their own radars and radar emission detectors (now called intercept receivers) it was too little, too late to influence the outcome of the war in their favor.

This chapter discusses the FMCW radar, radar waveform generation, and signal detection.

The radar ambiguity function is defined as the absolute value of the envelope of the output of a matched filter when the input to the filter is a Doppler-shifted version of the original signal, to which the filter was matched. Ambiguity functions are usually analyzed on a single pulse basis. Hence, in a work of this nature on continuous wave (CW) radars, there is no error as the results apply equally well to CW radar waveforms. However, in CW radars there is in advantage not shared by modulated pulsed radars, viz. the concept of periodic ambiguity function (PAF). The concept of PAF introduces the fact that in certain class of phase-coded signals employed in CW radars, one can obtain an autocorrelation function devoid of side lobes on the delay axis.

In this chapter, we have studied LFM waveform compression using correlation and stretch techniques. We then studied the basic FMCW radar theory and equations. We have also studied the effect of target Doppler on radar performance and how to measure it. We have then investigated the factors affecting range resolution like sweep times and beat frequency resolution. In particular, we have investigated problems like target return spectral width and receiver frequency resolution, which play such a key role in determining the beat frequency resolution which lead to our final receiver range bin resolution. Finally, through worked examples we investigated the problems pertaining to non-linearities and its control. In this process, we have investigated the trade-offs one needs to make between controlling the level (percentage) of non-linearities and the receiver frequency resolution leading to the final beat frequency resolution. This needs to be done without an excessive instrumented range in the radar. We shall use all this knowledge in Part III when we design the Pandora radar. We concluded this chapter by studying an interesting example of what can be achieved with FMCW technology in the area of antitank missiles.

In this chapter, we shall investigate the design and performance of phase-coded signals that have also found popularity in LPI radar waveform compression design. In the class of phase-coded signals, there is a wide variety. This class of signals transmits at one frequency, but changes the phase as it transmits in a predetermined order.

In this book we have reviewed two LPI radar signal waveforms, FMCW and phase-coded. The complexity of FMCW technology is minimal and it is very popular because of this reason. There are only two major obstacles that can be construed as a disadvantage in FMCW radars. These are the high time side lobes of the order of 13 dB down from the peak response and the nonlinearity in waveform generation for high bandwidths (and consequently high resolutions). The advantage of this waveform, however, lies in its Doppler tolerance, making it eminently suitable for use in aircraft target tracking radars. Phase-coded waveforms, on the other hand, are very easily adaptable to digital signal processing, being digital in nature, and polyphase codes produce relatively low time side lobes and as we have seen in some cases of polyphase codes, no time side lobes in the CW mode.

This chapter pertains to an FMCW navigation radar named Calypso. The name is the author's pseudonym for an actual FMCW navigational radar developed for navigation jointly by Philips Research Laboratory (PRL), Redhills, Surrey, England and Hollandse Signaal Apparaten B.V. (now Thales Netherlands B.V.), Hengelo, The Netherlands. This radar was the precursor of today's PILOT and Scout navigational radars. The contents of this chapter have been reproduced from and with permission. We shall examine issues like, power budget, noise figures, noise cancellation, ADCs, calibration and verification, MTIs, and so forth. We shall also investigate issues like single antenna operation and reflected power cancellers (RPCs) as well as removal of range ambiguities.

In this chapter, we carry out our analysis based on LFM waveforms. However, SFWF can also readily be applied without any changes. The radar, in fact, can be made switchable between these two waveforms.

The Pandora radar can be classified as a new class of target recognition radars for target identification well beyond visual range and can be slaved to a tracking radar or used as a surveillance radar in its own right. It is pointed out that target recognition is the primary quest for ultra-wide band radars. As yet there are massive technical problems that need to be overcome in this area, especially in the designing of cheap, high-power, extremely narrow pulse generators, while the Pandora appears already commercially viable. Hence, as target recognition radar, it will remain competitive for many years to come. It can also be used in a pulsed mode as a signal source for pulsed radar. This is possible, because of the parallel nature of the architecture. In such a mode, it can be used to generate large bandwidth step frequency signals or LFM many orders faster than is possible given the present state of technology. This will reduce Doppler smearing when tracking fast targets. In pulsed mode or CW mode, the Pandora is capable of superior performance in the presence of high target Doppler or own platform Doppler. Once the own Doppler is nulled (ODN), or at least brought down to a low value, it is possible to use it on fast flying platforms to carry out mapping activities, for example, airborne surveillance/planetary probes. This is because of the Doppler resilience of the LFM waveform. Such performance is difficult to obtain with relatively poor Doppler tolerant phase-coded signals.

In this chapter, we shall first review some of the basic parameters of the design of the SFCW radar and then examine the overall concept of Pandora, its working principle, and some of the key technologies that go into its design. We shall then discuss some of the experimental results achieved during their implementation.

The program 'cw.cpp' calculates the range/power levels of FMCW and phase-coded CW radars given either of the parameters. It outputs the range in kilometers or the average power in watts. It is intended as a tool for quick performance evaluation of CW radars.

We will now examine the procedure we need to adopt in the design of the eight-channel Pandora. This radar will essentially operate in two modes, the coarse mode and the line mode. The initial detection of the target will be in the coarse mode, wherein only one channel will be used and the target recognition will occur in the line mode wherein all eight channels will be used. We will examine these separately. The program “pandora.cpp” supplied with this book, gives you the initial option of starting with either of these modes. This is because the coarse mode also pertains to the design of a single-channel FMCW radar of the type as discussed in Chapter 7. The line mode pertains to the multi-channel radar and is meant for range profiling. In our example in this appendix, we will design separately for this coarse mode as well as the line mode.

The following proposal envisages a hardware solution to the range resolution problem. We shall first examine the mathematical expression for FMCW radar returns.

It was discussed in earlier chapters that the nonlinearities in the FM waveform need to be controlled to ensure against deterioration of range resolution. To illustrate the problem, let us examine the results of the line mode analysis given at Appendix B. We reproduce the results here for convenience.

The problem of transmit-receive noise leakage is known as one of the most severe problems facing the FMCW radar designer. The FM sidebands at a deviation of ωm like AM (amplitude modulation) noise sidebands at the same frequency give rise to noise also, but only at an IF of ωm. There is thus a simple relationship between the transmitter's noise spectra and the spectrum of the detected noise in the receiver's IF. Moreover, in the case where the frequency deviation is independent of frequency, that is, it is the same at all frequencies of interest, then it will be shown that the detected noise is the same at all IF frequencies, which is the same as the case for white AM noise. This derivation is based on the paper by Stove.

The author discusses the basic design considerations of the Pandora radar receiver system. The discussions pertain to one of the eight receiver tracts and the signal input is assumed to come from one receiver beam.

The discussion on DDS in this report is based on the paper by Kroupa and company manuals from Qualcomm and Stanford Telecom and reproduced here with permission.

This appendix contains the drawings leading to the implementation of the single-channel radar.

The aim of this appendix is to assess the Pandora radar performance through measurement. The measurements are necessary to confirm that the radar is behaving as predicted and that there is no deterioration in its performance. This radar has basically the following technological challenges: 1. Power combining 2. Power splitting 3. Group delay in filters.

The 8-way combiner intended for the Pandora radar is shown in Figure J-1. For the purposes of this analysis, the pin numbers are taken from 1 to 8 starting from the left. The output pin is pin number 9. This same combiner is used as a resolver in the receiver channel.

This appendix pertains to a GUI-based program developed by the author and supplied with the accompanying software. It supplies the .mat files and data vectors for running with the program supplied by Prof. Nadav Levanon. The program supplied with this book caters to the following polyphase codes: Frank codes; P1 code; P2 code; P3 code; and P4 code.

This appendix pertains to the level diagram calculations of the Pandora single-channel radar.