Achieving stealth requires minimizing the radar cross section (RCS) of a vehicle or system as it appears to an opponent’s radar detection capabilities. To achieve this objective, an active cancellation stealth system was designed by means of a phased-array technique, digital radio-frequency memory (DRFM), and field-programmable-gate-array (FPGA) technology. The DRFM enables precise replication of stored radar waveforms, while the phased-array technology is used to generate the required waveforms to cancel reflected radar returns. The FPGA is essential for signal analysis, database search, and waveform generation and control.

The system relies on an offline calculation approach in which omnidirectional RCS, clutter, and noise databases are established in advance. The active system’s signal processing and control module analyzes a measured radar signal parameter and then finds the corresponding target echo data in the RCS database, making a real-time adjustment of the coherent echo amplitude and phase parameters. By creating a target scattering field with coherent signal cancellation in the direction of a detecting radar system, the radar receiver remains in a null synthesis pattern. A combination of software and hardware helps realize this active cancellation stealth approach.

Radar stealth technology can be divided into passive and active techniques. Although passive methods have been traditionally used, the availability of high-speed microelectronic devices, phased-array antenna techniques, and computer processing have made active methods more feasible and practical. An active stealth system can adapt to almost any object that must be protected, such as a power plant or aircraft, and the technology can be retrofit to an existing electronics platform, with lower power consumption and other advantages compared to passive approaches.1

An active cancellation stealth system involves the use of coherent signal interference. For a target to avoid detection, it must emit a cancellation wave that is time-coincident with an incoming pulse, providing the required amplitude and phase to cancel the reflected energy from an enemy radar. This can be an effective means of blanking enemy radar pulses, although the difficulty in implementing such a system lies in the need to obtain cancellation signal parameters in real time, and to achieve precise control of the amplitude and phase of the cancellation waveform.2

Active cancellation stealth depends on adaptive real-time control of electromagnetic (EM) waveforms within a three-dimensional (3D) space. When a radar target is illuminated, return signals are produced by the target’s reflected radiation.

According to EM inverse scattering theory, if the source distribution of the radiation field is known, the properties of the scatterer and the scattering field distribution can also be known. If the radar signals are considered confined within a small solid angle for the sake of EM wave cancellation, a target can made to appear “invisible” or stealth to a radar system.

An important part of developing an active cancellation stealth system is understanding a given target’s RCS, which is a comparison of the scattered power density at the radar receiver with the incident power density at the target. The formal definition of RCS is3:

where:
σ0.5 = the complex root of the RCS
scatterer;
Ei = the electric field strength of the incident wave impinging on the target;
R = the distance between the radar and the scatterer;
êr = a unit vector aligned along the electric polarization of the receiver; and
ĒS = the vector of the scattered field.

Using either active or passive means, the principle of cancellation or reducing the RCS relies on reducing the field strength incident on the target to reduce the power reflected back to the radar receiver. Reducing the target scattering intensity can also reduce the RCS. A target’s RCS can be measured for different scattering directions and, according to Eq. 1, the direction of a radar target’s scattered field can be identified as:

ES = lim [Ei ∙ √σ ∙ êr)2√πR] (2)

Active cancellation methods are based on generating an EM field equal to a target’s scattered field, but with opposite phase. The effectiveness of active radar cancellation depends on the measurement precision of the radar signal, the knowledge of its real-time characteristics, and the accuracy of the generated cancellation field, among other factors. Figure 1 shows the principle of an active cancellation stealth process. The incident radar wave frequency, phase, amplitude, waveform characteristics, polarization, and radar space position are quickly and accurately measured by a reconnaissance antenna and signal processing system on the target platform.

The target reflection characteristics that correspond to the incident radar waveform must then be extracted from the target RCS database under the control of the computer information processing system. By generating a waveform with the appropriate parameters, including frequency, phase, intensity, and polarization, the target echo can be cancelled when the radar wave returns to its receiving antenna.

If a target can be resolved into a collection of N discrete scatterers or scattering centers, then the net radar return at a given frequency is:4

where:
σn = the RCS of the nth scatterer and
φn = the relative phase of the scatterer’s contribution due to its physical location in space.

For a target with a large number of scattering centers, several dominant scattering centers will exist for a specific operating radar frequency and incident signal angle. Reducing the radar returns from these dominant centers can effectively reduce the RCS of the target. If the original target RCS is defined as σ0, an active cancellation system can introduce an equivalent scattering center with effective RCS of σ1. The phases of these scattering centers are φ0 and φ1, respectively. The superposition of both for the target RCS is given by Equation 4:

Namely:

Control of σ1 and φ1can be used to optimize these parameters to obtain:

where parameter σ = 0 indicates having achieved stealth in the direction of the enemy radar.

Compiling a target RCS database is an essential step in designing an active cancellation stealth system. Each RCS entry represents a function, rather than simply a number, varying with different incident signal direction, frequency, and polarization. It may be necessary to establish an RCS database corresponding to different directions, frequencies, and polarizations according to real-time measurements of incident signal direction, frequency, polarization, and power from relevant data. This database must support real-time adjustment of transmitter parameters to generate an effective cancellation wave for transmission.

The capability of making real-time measurements of every radar signal incident on the target is also essential to creating an active cancellation stealth system. Also, the system must be capable of real-time tracking of such things as the relative motion between the detection radar and the desired stealth target, so that the cancellation signal has the proper parameters under dynamic conditions.

A received radar signal can be analyzed in several ways. It can be channeled into the digital-signal-processing and control unit for analysis. Alternately, it can be sent to the forwarding mode active system (used for storage and reproduction of received radar signals), where it can be compared to stored waveforms to find a corresponding signal. Dynamic corrections within the forwarding mode active system can ensure that the echo signal is consistent with the received radar signal. The output signal is then processed by means of Doppler frequency-shift modulation, with coherent superposition of noise and clutter. The power synthesis and beam-forming network and transmitting antenna are then used to form the active cancellation wave.

An active cancellation system structure is shown in Fig. 2. The reconnaissance receiver is used mainly for reconnaissance and reception of radar signals from enemy transmitters. The forwarding mode active system consists of five components: the DRFM, digital phase shifter, digital attenuator, adder, and detector (Fig. 3). The DRFM stores a received radar signal and copies it with high precision. The signal passes through the digital attenuator for amplitude adjustment and the digital phase shifter for phase adjustment. It then travels to the adder to couple with the wave signal produced by the digital-signal-processing and control unit.

The results from the adder are sent to the detector and a DC voltage is sent to the digital-signal-processing and control unit through an analog-to-digital-converter (ADC) interface. When the detector has measured a minimum output value, the system has achieved a zero balance. At this point, the digital-signal-processing and control unit will send a command to the forwarding mode active system, so that the radar signal is transmitted to the Doppler frequency-shift modulation module.

The system’s memory is mainly used for storing the databases, including the target echo database, the noise database, and the clutter database. The system operates with the assumption that a radar echo consists of three parts: target echo, noise, and clutter. As a result, a radar echo signal can be idealized as follows5:

x(t) = s(t) +n(t) + c(t) (7)

where:

s(t) = the target echo signal;
n(t) = the noise signal; and
c(t) = the clutter signal.

Because a great deal of processing and calculation power is needed to determine the radar cancellation wave, it is difficult to achieve real-time calculations without pipeline delays. For this reason, an offline calculation approach is used to establish a target RCS database. The main RCS prediction method is based on the approximation for obtaining a complex target RCS; the error between the predicted value and the actual RCS value can be minimized within a few decibels.6 Approximate solutions to a target’s RCS can be found in a number of ways, including by geometric optics, physical optics, geometrical theory of diffraction, equivalent currents, and areal projection/physical optics.

The database for clutter and noise usually employs a Gaussian distribution of white noise, which can be generated by the Monte Carlo method. Clutter can include ground, sea, and weather variants, among others. Methods for modeling and calculating clutter and noise are detailed in refs. 7-13.

Clutter data is related to airborne altitude, aircraft speed, radar carrier frequency, radar point, radar pulse repetition frequency (PRF), and distance to target. To reduce this large amount of data when clutter data are calculated, aircraft altitude, speed, and radar frequency are fixed, and only radar point and PRF are changed.

The digital-signal-processing and control unit is an active cancellation system core module that is used mainly for radar signal analysis and processing, database searches, and control of other system modules. It is comprised of field-programmable-gate-array (FPGA) chips, using the design diagram shown in Fig. 4. FPGA1 is used for analysis of a received signal; it sends instructions about a signal to memory via a Peripheral Component Interconnect (PCI) interface control chip. Retrieved data are available to FPGA2 and FPGA3 through PCI connection. Based on the signal information obtained, the target echo and clutter generation module produces a variety of target echo and clutter signals. Because of the range of signals, the computing time may vary, so the first device to complete a calculation will send a data cache to the Double Data Rate 2 (DDR2 ) memory. An output is synthesized once the calculation is completed.

The Doppler frequency-shift modulation unit superimposes the Doppler frequency on the forwarding mode active system output signal to produce an effective Doppler shift in the radar wave. The Doppler unit can be used to reflect the relative position of the target to the incident radar. The power synthesis and beam-forming unit, following instructions from the digital-signal-processing and control unit, can form the desired digital beam. It can also switch off the receiving channel and turn on the transmitting channel, allowing transmission of the modified beam via the transmit antenna.

For the purpose of evaluation, the active cancellation stealth system was simulated using commercial software and the following conditions:

  1. The radar transmit signal is a coherent pulse train with modulation rate of 1 MHz.
  2. The simulation signal has a pulse width of 4 μs and PRF of 1 kHz.
  3. The target moves with uniform speed (in a straight line), with initial distance from the radar transmitter of 100 km, initial radial velocity of 300 m/s; elevation and azimuth angles of both 0 deg.; and target RCS of 2 m2 based on the Swelling II model.
  4. The reconnaissance reference pattern function is described by Eq. 8:

where:
κ0 = (cosΘ0)0.5 = the factor for control of the phased-array antenna beam gain with scanning angle variation;
θ0 = the beam scanning angle;
θ1 = the unbiased-beam mainlobe beamwdth of 3 dB;
θ2 = the unbiased-beam first sidelobe 3-dB beamwidth;
A = the unbiased-beam mainlobe gain value;
B = the unbiased-beam first sidelobe gain value;
a = 2.783;
a1 = πθ1/a = the unbiased-beam first zero (in rads); and
a1.5 = π(θ1 + θ2/a = the unbiased-beam first sidelobe peak point of view (in rads).

The three-dimensional EM pattern can be simplified into an azimuth and elevation pattern multiplication result. Namely:

F(θ, φ) = Fθ(θ)Fφ(φ) (9)

where:
Fθ(θ) = the azimuth pattern and
Fφ(φ) = the elevation pattern.

Assuming that the radar antenna vertical mainlobe beamwidth is 2 deg., the mainlobe gain is 40 dB, the first sidelobe width is 1 deg., and the gain is 9 dB, the 3D antenna pattern shown in Fig. 5 will be produced. The system can also be used for an electronic-countermeasures (ECM) function using an M x N rectangular array antenna with a reference pattern function described as:14

(θ, φ) = G(θ,φ)|E(θ, φ)||e(θ, φ)| (10)

where:
g(θ, φ) = the antenna pattern;
G(θ, φ) = the directivity factor, which only affects antenna gain variations;
E(θ, φ) = the array factor, which determines the beam shape;
e(θ, φ) = the array element factor, with e(θ, φ) ≈ 1;
θ = the azimuth angle on the array of spherical coordinates;
φ = the elevation angle on the array of spherical coordinates;
φ ∈ [0, π/2]; and
Θ ∈ [0, 2π].

Adjacent to the array element spacing of d = λ/2 in the x and y directions, E{Θ, φ) can be expressed as:

where:
k = 2π/λ = the wave number;
Imn = the weighting coefficient; and

where:
θ0, φ0 = a beam pointing vector.
If M = 51, N = 21, θ0 = 30 deg., φ0 = 20 deg., the 51 x 21 array antenna pattern shown in Fig. 6 will result. Figure 7 shows the spectrum of a coherent pulse train. Figure 8 shows the coherent pulse train superimposed on the clutter and noise waveform, with the target signal completely submerged under clutter and noise. Figure 9 shows a signal spectrum with the superposition of clutter and noise with the target signal. Figure 10 shows the effects of echo cancellation before (top) and after the cancellation waveform (bottom). The cancellation signal can be defined as:15

where:
ΔĒ = the cancellation residual field and
ĒS = the target scattering field.

When S = 0, complete stealth is realized. From Fig. 10, it can be seen that ΔĒmax = 6 x 10−2 dB and the corresponding cancellation signal, S, is 0.51 dB, so that the maximum radar detection range has been reduced to about 25% of the original value.

In conclusion, these simulation results show that an active cancellation system can greatly reduce the chance that a target will be detected. The approach can be applied to a number of different radio echo scenarios. The active cancellation stealth system presented here has a modular design for simplicity of maintenance.

References

  1. Wang Zirong, Yu Dabin, Sun Xiaoquan et al., “Survey of radar stealth technology,” Aerospace Shanghai, Vol. 3, 1999, pp. 52-56 (in Chinese).
  2. Qu Changwen and Xiang Yingchun, “Active cancellation stealth analysis based on RCS characteristics of target,” Radar Science and Technology, Vol. 4, 2010, pp. 109-112, 118 (in Chinese).
  3. E.F. Knott, Radar Cross Section, Artech House, Dedham, MA, 1985, p. 19.
  4. Wu Man-qing, “Development and future design of digital array radar,” Radar Science and Technology, Vol. 6, No. 6, 2008, pp. 401-405 (in Chinese).
  5. Xu Wenqiang, “Study on key technology of radar video echo simulation,” North University of China, Taiyuan, 2007, p. 9 (in Chinese).
  6. Liu Tian’an, “The simulation of radar target and environment echo signal,” Xi’an: Xidian University, Xi’an, 2011, p. 6 (in Chinese).
  7. Chen Aijun, “Radar echo signal simulation,” Nanjing Institute of Technology, Nanjing, 2004, p. 38.
  8. D.J. Browning and J.E. Summer, “Computer modeling of ground clutter in airborne radar,” IEE Colloquium on Radar System Modeling (Reference number 1998/459), Vol. 6, Chaps. 1-6, 1998.
  9. D.A. Shnidman, “Generalized radar clutter model,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 35, No. 3, July 1999, pp. 857-865.
  10. W.J. Szajnowski, “Simulation model of correlated K-distributed clutter,” Electronics Letters, Vol. 36, No. 5, March 2000, pp. 476-477.
  11. M. Rangaswamy and D. Weiner, “Computer generation of correlated non-Gaussian radar clutter,” IEEE Transactions on AES, Vol. 31, No. 1, 995, pp. 106-115.
  12. E. Conte and M. Longo, “On a Coheremt Model for Log-Normal Clutter,” IEE Proceedings, Part F, Vol. 134, No. 2, 1987, pp. 198-201.
  13. Gang Li and Kai-Bor Yu, “Modeling and Simulation of Coherent Weibull Clutter,” IEE Proceedings F, Vol. 136, No. 1, 1989, pp. 2-12.
  14. Wang Guoya, Wang Liandong, Wang Guoliang, et al., “Simulation and Evaluation fo Radar and Electronic Warfare Systems,” National Defense Industry Press, Beijing, 2004, pp. 95-96 (in Chinese).
  15. Liang Bai-Chuang, “Study on Active Stealth Technique, Journal of Shipboard Electronic Countermeasures, Vol. 27, No. 1, February 2004, pp. 6, 16.