Based on the zero correlation zone (ZCZ) concept, we present the definitions and properties of a set of new ternary codes, ZCZ sequence-Pair Set (ZCZPS), and propose a method to use the optimized punctured sequence-pair along with Hadamard matrix to construct an optimized punctured ZCZ sequence-pair set (OPZCZPS) which has ideal autocorrelation and cross-correlation properties in the zero correlation zone. Considering the moving target radar system, the correlation properties of the codes will not be severely affected when Doppler shift is not large. We apply the proposed codes as pulse compression codes to radar system and the simulation results show that optimized punctured ZCZ sequence-pairs outperform other conventional pulse compression codes, such as the well-known polyphase code—P4 code.
1. Introduction
Pulse compression is known as a technique to raise the signal to maximum sidelobe
(signal-to-sidelobe) ratio to improve the target detection and range resolution abilities
of the radar system. This technique allows a radar to simultaneously achieve the energy
of a long pulse and the resolution of a short pulse without the high peak power which
is required by a high energy short duration pulse [1]. One of the waveform designs suitable for pulse compression is phase-coded waveform
design. The phase-coded waveform design is that a long pulse of duration
is divided into
subpulses each of width
. Each subpulse has a particular phase, which is selected in accordance with a given
code sequence. The pulse compression ratio equals the number of subpulses
, where the bandwidth is
. In general, a phase-coded waveform with longer code word, in other words, higher
pulse compression ratio, can have lower sidelobe of autocorrelation, relative to the
mainlobe peak, so its main peak can be better distinguished. The relative lower sidelobe
of autocorrelation is very important since range sidelobes are so harmful that they
can mask main peaks caused by small targets situated near large targets. In addition,
the cross-correlation property of the pulse compression codes should be considered
in order to reduce the interference among radars when we choose a set of pulse compression
codes to work in a Radar Sensor Network (RSN).
Much time and effort was put for designing sequences with impulsive autocorrelation
functions (ACFs) and cross-correlation functions (CCFs) for radar target ranging and
target detection. On one hand, for aperiodic sequences, it is known that for most
binary sequences of length
the attainable sidelobe levels are approximately
[2, 3] and the mutual peak cross-correlations of the same-length sequences are much larger
and are usually in the order of
to
. Later, set of binary sequences of length
with autocorrelation sidelobes and cross-correlation peak values of approximately
are studied in paper [4]. Besides, the small set of Kasami sequences and the Bent sequences could achieve
maximum correlation values of approximately
. In addition to binary sequences, polyphase codes, with better Doppler tolerance
and lower range sidelobes such as the Frank and P1 codes, the Butler-matrix derived
P2 code, the linear-frequency-derived P3 and P4 codes were provided and intensively
analyzed in [5–7]. Quadiphase [8] code could also reduce poor fall-off of the radiated spectrum and mismatch loss
in the receiver pulse compression filter of biphase codes. Nevertheless, the range
sidelobe of the polyphase codes can not be low enough to avoid masking returns from
targets. Hence, considerable work has been done to reduce range sidelobes for the
radar system. By suffering a small
loss, the authors in [9] present several binary pulse compression codes to greatly reduce sidelobes. In the
previous paper [10], pulse compression using a digital-analog hybrid technique is studied to achieve
very low range sidelobes for potential application to spaceborne rain radar. In the
paper [11], time-domain weighting of the transmitted pulse is used and is able to achieve a
range sidelobe level of
55 dB or better in flight tests. These sidelobe suppression methods, however, degrade
the receiving resolution because of wider mainlobe.
On the other hand, for periodic sequences, the lowest periodic ACF that could be achieved
for binary sequences, as in the case of
-sequences [12, 13] or Legendre sequences, is
. GMW [14] has the same periodic ACF properties, but posses larger linear complexity. Considering
the nonbinary case, it is possible to find perfect sequences, such as two valued Golomb
sequences, Ipatov ternary sequences, Frank sequences, Chu sequences, and modulatable
sequences. However, it should be noted that for both binary and non-binary cases,
it is impossible for the sequences to have perfect ACF and CCF simultaneously although
ideal CCFs could be achieved alone. One can synthesize a set of non-binary sequences
with impulsive ACF and the lower bound of CCF:
,
[15, 16], which is governed by Welch bound and Sidelnikov bound.
So far in the previous work, range sidelobes could hardly reach as low as zero. In addition, it has also been well proven that it is impossible to design a set of codes with ideal impulsive autocorrelation function and ideal zero cross-correlation functions, since the corresponding parameters have to be limited by certain bounds, such as Welch bound [15], Sidelnikov bound [16], Sarwate bound [17], and Levenshtein bound [18]. To overcome these difficulties, the new concepts, generalized orthogonality (GO), also called Zero Correlation Zone (ZCZ) is introduced. Based on ZCZ [19–21] concept, we propose a set of ternary codes, ZCZ sequence-pair set, which can reach zero autocorrelation sidelobe zero mutual cross-correlation peaks during Zero Correlation Zone. We also present and analyze a method to construct such ternary codes and subsequently apply them to a radar detection system. The method is that optimized punctured sequence-pair joins together with Hadamard matrix to construct optimized punctured ZCZ sequence-pairs set. An example is presented, investigated, and studied in the radar targets detection simulation system for the performance evaluation of the proposed ternary codes. Because of the outstanding property performance and well target detection performance in simulation system, the newly proposed codes can be useful candidates for pulse compression application in radar system.
The rest of the paper is organized as follows. Section 2 introduces the definitions and properties of ZCZPS. In Section 3, the optimized punctured ZCZPS is introduced, and a method using optimized punctured sequence-pair and Hadamard matrix to construct such codes is given and proved. In Section 4, the properties and ambiguity function of optimized punctured ZCZPS are simulated and analyzed. The performance of optimized punctured ZCZPS is investigated in radar targets detection system by comparing with P4 code in Section 5. In Section 6, conclusions are drawn on optimized punctured ZCZPS.
2. Definitions and Properties of ZCZ Sequence-Pair Set
Zero Correlation Zone (ZCZ) is a new concept provided by Fan et al. [21, 22] in which the autocorrelation sidelobes and cross-correlation values are zero while the time delay is kept within ZCZ instead of the whole period of time domain. There has been considerable interest in constructing [23–27] new classes of ZCZ sequences in ZCZ and studying their properties [28].
Here, we introduce sequence-pair into the ZCZ concept to construct ZCZ sequence-pair
set. We consider ZCZPS
,
is a set of
sequences of length
and
is a set of
sequences of the same length
:
(1)The autocorrelation function (ACF) (here we use autocorrelation to stand for the cross-correlation
between two different sequences of a sequence-pair to distinguish the cross-correlation
between two different sequence-pairs) of sequence-pair
is defined by
(2)The cross-correlation function of two sequence-pairs
and
,
is defined by
(3)where
is the time delay and
is the bit duration.
For pulse compression sequences, some properties are of particular concern in the
optimization for any design in engineering field. They are the peak sidelobe level,
the energy of autocorrelation sidelobes, and the energy of their mutual cross-correlation
[4]. Therefore, the peak sidelobe level which represents a source of mutual interference
and obscures weaker targets can be presented as
,
is among the zero correlation zone for ZCZPS. Another optimization criterion for
the set of sequence-pairs is the energy of autocorrelation sidelobes joined together
with the energy of cross-correlation. By minimizing the energy, it can be distributed
evenly, and the peak autocorrelation sidelobe and the cross-correlation level can
be minimized as well [4]. Here, the energy of ZCZPS can be employed as
(4)According to (4), it is obvious to see that the energy can be kept low while minimizing the autocorrelation sidelobes and cross-correlation values of any two sequence-pairs within Zero Correlation Zone.
Hence, the ZCZPS can be constructed by minimizing the autocorrelation sidelobe of a sequence-pair and cross-correlation value of any two sequence-pairs in ZCZPS.
Definition 1.
Assume
to be a sequence-pair set of
sequence-pairs and each sequence-pair is of
bit length. If all the sequence-pairs in the set satisfy the following equation:
(5)where
,
,
and
. Then
is called a ZCZ sequence-pair,
is an abbreviation, and
is called a ZCZ sequence-pair set,
is an abbreviation.
3. Optimized Punctured ZCZ Sequence-Pair Set
3.1. Definition of Optimized Punctured ZCZ Sequence-Pair Set
Matsufuji and Torii have provided some methods of constructing ZCZ sequences in [29, 30]. In this section, a set of novel ternary codes, namely, the optimized punctured ZCZ sequence-pair set, is constructed by applying the optimized punctured sequence-pair [31] to the Zero Correlation Zone. Here, optimized punctured ZCZPS is a specific kind of ZCZPS.
Definition 2 (see [31]).
Sequence
is the punctured sequence for 
(6)where
is the number of punctured bits in sequence
. Suppose
and
,
is
-punctured binary sequence,
is called a punctured binary sequence-pair.
Definition 3 (see [31]).
The autocorrelation of punctured sequence-pair
is defined as
(7)If the punctured sequence-pair has the following autocorrelation property:
(8)the punctured sequence-pair is called an optimized punctured sequence-pair [31]. Where,
, is the energy of punctured sequence-pair.
Definition 4.
If
in Definition 1 is constructed by optimized punctured sequence-pair and a certain
matrix, such as Hadamard matrix or an orthogonal matrix, where
(9)Then
(10)where
and
, then
can be called an optimized punctured ZCZ sequence-pair set.
is an abbreviation.
3.2. Design of Optimized Punctured ZCZ Sequence-Pair Set
Based on an optimized punctured binary sequence-pair of odd length and a Hadamard matrix, an optimized punctured ZCZPS can be constructed on following steps.
Step 1.
Considering an optimized punctured binary sequence-pair
of odd length, the length of each sequence is
:
(11)Step 2.
A Hadamard matrix
(the Hadamard matrix is made up of a set of Walsh sequences) of order
is used here.
, the length of each sequence, is equal to the number of the sequences in the matrix.
Here, any Hadamard matrix order is possible and
is the row vector of the matrix:
(12)Step 3.
Doing bit-multiplication on the optimized punctured binary sequence-pair and each
row of the Hadamard matrix B, then sequence-pair set
is obtained,
(13)Here, the optimized punctured binary sequence-pairs are of odd lengths and the lengths
of Walsh sequence are
,
It is easy to see that
, common divisor of
and
is 1, then
. The sequence-pair set
is the optimized punctured ZCZPS and
is the Zero Correlation Zone
. The length of each sequence in optimized punctured ZCZPS is
that depends on the product of length of optimized punctured sequence-pair and the
length of Walsh sequence in Hadamard matrix. The number of sequence-pairs in optimized
punctured ZCZPS rests on the order of the Hadamard matrix. The sequence
in sequence set
and the corresponding sequence
in sequence set
construct a sequence-pair
that can be used as a pulse compression code.
The correlation property of the sequence-pairs in optimized punctured ZCZPS is
(14)where
is the Zero Correlation Zone
and
.
Proof.
(
) When
,
(15)(
) When
,
(16)According to Definition 1, the OPZCZPS constructed by the above method is a ZCZPS.
4. Properties of Optimized Punctured ZCZ Sequence-Pair Set
Considering the optimized punctured ZCZPS constructed by the method mentioned in the
last section, the autocorrelation and cross-correlation properties can be simulated
and analyzed. For example, the optimized punctured ZCZPS
is constructed by 31-length optimized punctured binary sequence-pair
,
,
(using "
'' and "
'' symbols for "
'' and "
'') and Hadamard matrix
of order 4. We follow the three steps presented in Section 3.2 to construct the optimized
punctured ZCZPS. The number of sequence-pairs here is 4, and the length of each sequence
is
. The first row of each matrix
and
constitute a certain optimized punctured ZCZP
. Similarly, the second row of each matrix
and
constitute another optimized punctured ZCZ sequence-pair
, and so on:
(17)Here, optimized punctured ZCZ sequence-pairs
and
are studied as two examples in the following parts.
4.1. Autocorrelation and Cross-Correlation Properties
The autocorrelation property and cross-correlation property of 124-length sequence-pairs
in the optimized punctured ZCZ sequence-pair set
are shown in Figures 1 and 2.
Figure 1. Periodic autocorrelation property of optimized punctured ZCZPS.
Figure 2. Periodic cross-correlation property of optimized punctured ZCZPS.
From the Figures 1 and 2, the peak autocorrelation sidelobe of ZCZPS and their cross-correlation value are
kept as low as zero while the time delay is kept within
(Zero Correlation Zone). And it is always true that the cross-correlation values
of optimized punctured ZCZPS and the autocorrelation sidelobe could be kept as low
as zero during ZCZ.
We still have to confess that the energy loss of the proposed codes is no less than
1.7 db due to reference mismatch. However, the perfect periodic ACF and CCF achieved
simultaneously during the ZCZ zone and the codes' structure could make up for it.
It is known that a suitable criterion for evaluating code of length
is the ratio of the peak signal mainlobe divided by the peak signal sidelobe (PSR)
of their autocorrelation function, which can be bounded by [32]
(18)The only aperiodic uniform phase codes that can reach the
are the Barker codes whose length is equal or less than 13. Considering the periodic
sequences, the
-sequences or Legendre sequences could achieve the lowest periodic ACF of
. For non-binary sequences, it is possible to find perfect sequences of ideal ACF.
Golomb codes are a kind of two valued (biphase) perfect codes which obtain zero periodic
ACF but result in large mismatch power loss. The Ipatov code shows a way of designing
code pairs with perfect periodic autocorrelation (the cross-correlation of the code
pair) and minimal mismatch loss. In addition, zero periodic autocorrelation function
for all nonzero shifts could be obtained by polyphase codes, such as Frank and Zadoff
codes. However, for both binary and non-binary periodic sequences, it is not possible
for the sequences to have perfect ACF and CCF simultaneously although ideal CCFs could
be achieved alone. Comparing with the above codes, the proposed ternary codes could
obtain perfect periodic ACF during the ZCZ and the reference sequence is made of
which is much less complicated than other perfect ternary codes such as Ipatvo code.
The reference code for Ipatov code is of a three-element alphabet which might not
always be integer.
Nevertheless, considering multi targets in the system, multiple peaks of the autocorrelation
function of the proposed codes might affect on the range resolution. The range resolution
could be limited as
or
. Here,
is one bit duration,
is the length of an optimized punctured sequence-pair and
is the length of an optimized punctured ZCZ sequence-pair. In the Figure 1,
. Otherwise, some digital signal processing methods could also be introduced to distinguish
the peaks. On the other hand, there may also be the concern that multiple peaks of
single transmitting signal reflected from one target may affect determining the main
peak of ACF. As a matter of fact, the matched filter here could shift at the period
of ZCZ length to track each peak instead of shifting bit by bit after the first peak
is acquired. Hence, in this way could it be working more efficiently. Alike the tracking
technology in synchronization of CDMA system, checking several peaks instead of only
one peak guarantee the precision of
and avoidance of
. In addition, those obtained peaks could be averaged before the detection in order
to reduce the effect of random noise in the channel so that the detection performance
could be improved.
To sum up, the new code could achieve perfect ACF and CCF in the ZCZ simultaneously according to Figures 1 and 2, and its PSR can be as large as infinite.
4.2. Ambiguity Function
When the transmitted impulse is reflected by a moving target, the reflected echo signal
includes a linear phase shift which corresponds to a Doppler shift
[32]. As a result of the Doppler shift
, the main peak of the autocorrelation function is reduced. The SNR is degraded and
the sidelobe structure is also changed because of the Doppler shift.
The ambiguity function which is usually used to analyze the radar performance within Doppler shift and time delay is defined in [32]:
(19)where
is the time delay between transmitting signal and matched filter, and
is the Doppler shift.
In [33], Periodic Ambiguity Function (PAF) is introduced by Levanon as an extension of the periodic autocorrelation for Doppler shift. And the single-periodic complex envelope is [34]
(20)where
is one period of the signal.
We are studying sequence-pairs in this research, so we use different codes for transmitting part and receiving part. The single-period ambiguity function for ZCZPS can be rewritten as
(21)where
,
is one period of the signal and
is one bit duration. At the same time, when
, (21) can be used to analyze the autocorrelation property within Doppler shift, and
when
, (21) can be used to analyze the cross-correlation performance within Doppler shift.
Equation (21) is plotted in Figure 3 in a three-dimensional surface plot to analyze the radar performance of optimized
punctured ZCZPS within Doppler shift. Here, maximal time delay is 1 unit (normalized
to length of the code, in units of
) and maximal Doppler shift is 5 units for cross-correlation and 3 units for autocorrelation
(normalized to the inverse of the length of the code, in units of
).
Figure 3. Ambiguity function of 124-length ZCZPS: (a) autocorrelation, (b) cross-correlation.
In Figure 3(a), there is relative uniform plateau suggesting low and uniform sidelobes. This low
and uniform sidelobes minimize target masking effect in Zero Correlation Zone of time
domain, where
,
. From Figure 3(b), considering cross-correlation property between any two optimized punctured ZCZ sequence-pairs
of the ZCZPS, we can see that the optimized punctured ZCZPS is tolerant of Doppler
shift when Doppler shift is not large. When the Doppler shift is zero, or the target
is not moving, cross-correlation of our proposed code is zero during ZCZ.
Since synchronizing techniques develop exponentially in the industrial world, time
delay between transmitting signal and matched filter can, to some extent, be precisely
estimated. Therefore, it is necessary to investigate the property of our proposed
code when we have the output of the matched filter at the expected time
. When
, the ambiguity function can be expressed as
(22)And the Doppler shift performance without time delay is presented in the Figure 4.
Figure 4. Doppler shift of 124-length ZCZPS (
): (a) autocorrelation (b) cross-correlation.
Figure 4(a) illustrates that without time delay of matched filter but having the Doppler shift
less than 1 unit, the autocorrelation value of optimized punctured ZCZPS falls sharply
during one unit, and the trend of the amplitude over the whole frequency domain decreases
as well. Figure 4(b) shows that there are some convex surfaces in the cross-correlation performance. From
Figures 4(a) and 4(b), when Doppler frequencies equal to multiples of the pulse repetition frequency (
), all the ambiguity values turn to zero except when Doppler frequency is equal to
2 PRF for cross-correlation. That is the same as many widely used pulse compression
binary code such as the Barker code. Overall, the ambiguity function performances
of optimized punctured ZCZP can be as efficient as conventional pulse compression
binary code.
5. Application to Radar System
According to [32], Probability of Detection (
), Probability of False Alarm (
) and Probability of Miss (
) are three probabilities of most interest in the radar system. Note that
. Therefore, we simulated the above three probabilities of using 124-length optimized
punctured ZCZ sequence-pair in radar system in this section. The performance of radar
system using 124-length P4 code is also studied in order to compare with the performance
of optimized punctured ZCZ sequence-pairs of corresponding length. In the simulation
model,
times of Monte-Carlo simulation has been run for each SNR value. The Doppler shift
frequency is a random variable that is kept less than 1 unit (normalized to the inverse
of the length of the code, in units of
), and the expected peak time of the output of the matched filter is at
.
From Figure 5, the probabilities of miss target detection
of the system using 124-length optimized punctured ZCZP are lower than 124-length
P4 code especially when the SNR is not high. When SNR is higher than 18 dB, both probabilities
of miss targets of the system approach zero. However, the probabilities of miss targets
of P4 code fall more quickly than optimized punctured ZCZP.
Figure 5. Probability of miss targets detection: 124-length optimized punctured ZCZ sequence-pair
versus 124-length P4 code.
We plotted the detection probability
versus false alarm probability
of the coherent receiver. We have simulated the performance at different SNR values.
Because of the limited space, we only chose SNR at 12 db and 14 dB. Figure 6 shows performance of 124-length optimized punctured ZCZP and performance of the same
length P4 code when the SNR is 12 dB and 14 dB. Within the same SNR value either 12 dB
or 14 dB, the detection probabilities of optimized punctured ZCZ sequence-pair are
much larger than detection probabilities of P4 code, and meanwhile
of the first code are also smaller than
of the latter code. Stating differently, optimized punctured ZCZ sequence-pair has
higher target detection probability while keeping a lower false alarm probability.
Furthermore, observing Figure 6, 124-length optimized punctured ZCZ sequence-pair even has much better performance
at 12 dB SNR than P4 code of corresponding length at 14 dB SNR.
Figure 6. Probability of detection versus probability of false alarm of the coherent receiver:
124-length optimized punctured ZCZ sequence-pair versus 124-length P4 code.
6. Conclusions
The definition and properties of a set of newly provided ternary codes-ZCZ sequence-pair set were discussed in this paper. Based on optimized punctured sequence-pair and Hadamard matrix, we have investigated a constructing method for a specific ZCZPS-optimized punctured ZCZPS made up of a set of optimized punctured ZCZPs along with studying its properties. The significant advantage of the optimized punctured ZCZPS is the considerably reducedn autocorrelation sidelobe and zero mutual cross-correlation value during ZCZ. According to the radar system simulation results shown in Figures 5 and 6, it is easy to observe that 124-length optimized punctured ZCZPS has better performance than P4 code of the same length when the target is not moving very fast in the system. A general conclusion can be drawn that the optimized punctured ZCZPS consisting of optimized punctured ZCZ sequence-pairs can effectively increase the variety of candidates for pulse compression codes. Because of the ideal cross-correlation properties of optimized punctured ZCZPS, our future work would focus on the application of the optimized punctured ZCZPS in multiple radar systems.
Acknowledgments
This work was supported in part by the National Science Foundation under Grants CNS-0721515, CNS- 0831902, CCF-0956438, CNS-0964713, and Office of Naval Research (ONR) under Grant N00014-07-1-0395 and N00014-07-1-1024.
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