This paper was edited by Chinthaka Gooneratne.

The exploitation of coherency gain and diversity gain to improve the MIMO system performance is a burning research topic. This paper is to examine the performance analysis of MIMO radar by utilizing the above-said gains. The authors have analyzed the performance of the MIMO radar, in terms of mathematical modeling, considering the probability of detection and post-processing SNR, with respect to changes in the diversity order. Furthermore, this paper also deals with the practical implementation and analysis of the said system, demonstrating the range imaging and RCS pattern of a known standard target.

Multiple input multiple output (MIMO) radar draws the attention of the researchers at the background of MIMO communication. Detection, target characterization and tracking are the basic functions of a radar system. But environmental conditions (multipath, clutter) and a low signal-to-noise ratio (SNR) put lots of challenges among many challenges faced by any radar system (

In MIMO radar, targets are probed with multiple, simultaneous waveforms, relying on the characteristic of the transmitted waveform, and joint signal processing of the target return signal using multiple receive antennas. MIMO radar utilizes a large number of degrees of freedom to boost the system performance over the conventional radar. MIMO radar systems may have collocated (

Contributions of this study are listed as follows:

This paper deals with the development and analysis of the software-defined radio-based (SDR) radar system for the target aspect angle pattern characterization. Aspect angle measurement is one of the important radar parameters considered for target characterization.

Authors apply the concept of the spread spectrum for developing the radar system. It is well known that the spread spectrum coded system possesses a low probability of intercept (LPI). Thus, it will make the radar system more superior. The spread spectrum system requires proper choice of waveform. Hence, the design of proper waveform is being considered and analyzed on the basis of the parameters like range resolution, side lobe level, Doppler resolution, Doppler side lobe level, etc.

Furthermore, the development of the distributed MIMO system is considered due to its advantage of improving the resolution of the target detection over other available antenna configuration systems. Here, the signals returned from target are processed coherently, which requires proper phase synchronizing.

Then a hybrid spread spectrum with the MIMO architecture radar system is developed and its performance is analyzed on the basis of simulation. In the simulation, the probability of detection and post-processing SNR levels of the signals have been analyzed and compared with respect to the change in the number of antennas.

The developed radar system is then implemented on both single antenna-based stand-alone instrumentation system and multi antenna-based SDR platform. The testing is done over the open range so as to reflect the system performance under jamming and fading channel condition. The system’s performance is analyzed on the basis of target characterization (i.e. aspect angle pattern) of a known standard target like flat plate.

The rest of the paper is organized as follows. Section “Mathematical model” represents a mathematical analysis of the probability of detection and post-processing SNR for MIMO radar. Section “Simulation results” represents the simulated results, which include the comparison of the probability of detection and post-processing SNR for MIMO radar with the change in transmitter and receiver antennas. The next section “Hardware results” produces the hardware implementation of the single input single output (SISO) radar system and MIMO radar. Section “Conclusion” concludes the paper.

Let us consider the radar detection problem at the delay

_{0}: Fall detection.

_{1}: Target detected.

Based on the Neyman–Pearson sense, the optimal detector likelihood ratio test (LRT) can be given as (_{0}) and _{1}) are the probability density function of observation corresponding to the radar detection hypotheses and _{th} is a threshold, which is governed by the probability of false alarm. Here, the received signal model is represented by

For the analysis purpose, in this paper we have considered

Now for the MIMO system, the distribution of the test statistic (^{2} random variable having

The probability of false alarm can be expressed as follows:

The probability of detection is given by the following:

As in the study of

For MIMO radar, (_{0}) = _{n})^{2} and:

And also:

Therefore, using E

In this section, we consider different configurations of the MIMO system to analyze the system performance. All the simulation results have been done using MATLAB software. Here, the probability of the detection (_{d}) and the output signal SNR after the MIMO signal processing have been studied.

MIMO radar probability of detection variations with respect to the antenna variation.

MIMO radar output SNR variations with respect to the antenna variation.

Therefore, from these two numerical results, one can conclude that diversity order plays an important role in enhancing the performance of a MIMO system. MIMO radar exploits the target angular spread to combat target fading. MIMO radar observes a different aspect of the target, enabling the MIMO radar to exploit spatial diversity to overcome target fading. The diversity order is directly proportional to the number of the antennas and the same is visible here in the results.

It is reasonable to point out that although MIMO radar offers many advantages, but from the point of view of the implementation, MIMO radar is considerably more complex and costly than the monostatic radar. Therefore, this puts some limitations on the number of antennas that can be used.

The authors have taken the double-folded approach for the development of the radar setup. First, the authors have taken stand-alone hardware such as arbitrary waveform generator (AWG), vector signal analyzer (VSA) for the design of the transmitter and receiver section. And the vector signal generator (VSG) is used as RF frequency generator. Second, after parameter finalization through the rigorous experimentation, the total system has been realized in the miniaturized version using the SDR platform with multiple antennas.

In the stand-alone approach as in

Radar setup with stand-alone instruments.

The baseband signal has the following specifications: No. of bits: 25 bits P4 code; Duty cycle: 35%; Ton = 5 micro sec; Toff = 9.28 micro sec. Then the IF signal is upconverted to the RF frequencies (0.3–3.0 GHz) by using a vector signal generator (VSG) as RF frequency generator. For the transmission and reception, Horn antenna has been used. The target under the test (TUT) is placed on a three-axis rotating pylon. At the receiver side, all the radar signal processing algorithms have been performed in VSA. Here, the authors have used two-channel VSA; one channel is used to take the reference signal and another channel is used for the received signal. In VSA, with the help of the correlation processing between the received and reference signal, the target detection has been carried out. The entire system is designed in LabView platform.

As a part of system validation, initially, only the range imaging has been considered. As we know that the range resolution depends on the signal bandwidth, here, we have considered a swept bandwidth of 1 GHz for having the resolution of 0.15 meter. Now, to have the swept bandwidth of 1 GHz, we have swept the RF frequency from 1.5 GHz to 2.5 GHz. For the experimentation purpose, the target is kept at a distance of 162 meters. The Tx and Rx antenna height is 18 feet and Pylon height is 16.5 feet.

(A) Spectrum of the reference signal at VSA; (B) reference signal at VSA.

(A) Spectrum of the received signal at VSA; (B) received signal at VSA.

(A) Radar test range; (B) flat plate (target) placed over Pylon.

Range measurement.

As mentioned in the introduction section, MIMO exploits the spatial diversity to combat the channel fading effect, thereby enhancing the system performance. Therefore, as its extension, the authors have implemented the MIMO radar and the performance of the same has been tested in the same open range, as presented in the next section.

Here, as reconfigurable hardware, Wireless-Access Research Platform (WARP) SDR is used, which has a Xilinx Xilinx Virtex-6 LX240T FPGA along with 2 Radio daughter Cards. Dual-band RF option (2,400–2,500 MHz, 4,900–5,875 MHz) is available, and 2.4 GHz is selected as the carrier frequency for this radar development. The maximum available RF bandwidth is 40 MHz. Available TX power is 30 dB and the Rx gains’ control range is 93 dB. This board can be interfaced with Laptop using a LAN protocol. The baseband P4 code generation, data transmission, data reception and WARP board control code are written in MATLAB. And after receiving the signal, all the receiver signal processing algorithms have been performed in the MATLAB environment (

WARP SDR hardware platform (

Here, the authors have used two SDR platforms in order to design a 2 × 2 MIMO system; one SDR platform has been used to design the transmitter section with two transmitting antennas, and the other one is used to design two channel MIMO radar signal processing. At the receiver side, two signals are coherently added and then passed through the correlation processing for the detection and characterization purpose. A typical radar setup with the SDR kits is shown below. As in the figure, we have used two horn antennas (frequency of operation: 1.7 GHz–2.7 GHz) both at the transmitter and the receiver section (

2 × 2 MIMO radar setup.

(A) Transmitted signal from SDR platform; (B) received signal at the SDR platform.

Target characterization using 2 × 2 MIMO radar.

This paper deals with the development of the MIMO radar. As presented here, the diversity order increases with the increase in the number of antennas, and this leads to an increase in the probability of detection and also the post-processing SNR level of the received signal. Therefore, one can conclude that MIMO radar significantly improves radar performance. In order to have an intuitive aspect of the performance of the MIMO radar, the experimental result has been presented in terms of the flat plate pattern, where the experimental pattern is nearly identical to the theoretical pattern.